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At least 1,063 records · Page 59

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DOE OSTI2013

Rapid Automated Dissolution and Analysis Techniques for Radionuclides in Recycle Process Streams

The analysis of process samples for radionuclide content is an important part of current procedures for material balance and accountancy in the different process streams of a recycling plant. The destructive sample analysis techniques currently available necessitate a significant amount of time. It is therefore desirable to develop new sample analysis procedures that allow for a quick turnaround time and increased sample throughput with a minimum of deviation between samples. In particular, new capabilities for rapid sample dissolution and radiochemical separation are required. Most of the radioanalytical techniques currently employed for sample analysis are based on manual laboratory procedures. Such procedures are time- and labor-intensive, and not well suited for situations in which a rapid sample analysis is required and/or large number of samples need to be analyzed. To address this issue we are currently investigating radiochemical separation methods based on extraction chromatography that have been specifically optimized for the analysis of process stream samples. The influence of potential interferences present in the process samples as well as mass loading, flow rate and resin performance is being studied. In addition, the potential to automate these procedures utilizing a robotic platform is evaluated. Initial studies have been carried out using the commercially available DGA resin. This resin shows an affinity for Am, Pu, U, and Th and is also exhibiting signs of a possible synergistic effects in the presence of iron.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Arctic Clouds Infrared Imaging Field Campaign Report

The Infrared Cloud Imager (ICI), a passive thermal imaging system, was deployed at the North Slope of Alaska site in Barrow, Alaska, from July 2012 to July 2014 for measuring spatial-temporal cloud statistics. Thermal imaging of the sky from the ground provides high radiometric contrast during night and polar winter when visible sensors and downward-viewing thermal sensors experience low contrast. In addition to demonstrating successful operation in the Arctic for an extended period and providing data for Arctic cloud studies, a primary objective of this deployment was to validate novel instrument calibration algorithms that will allow more compact ICI instruments to be deployed without the added expense, weight, size, and operational difficulty of a large-aperture onboard blackbody calibration source. This objective was successfully completed with a comparison of the two-year data set calibrated with and without the onboard blackbody. The two different calibration methods produced daily-average cloud amount data sets with correlation coefficient = 0.99, mean difference = 0.0029 (i.e., 0.29% cloudiness), and a difference standard deviation = 0.054. Finally, the ICI instrument generally detected more thin clouds than reported by other ARM cloud products available as of late 2015.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for the purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and accounted for. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked. Infrared, laser or stereoscopic vision sensors are all options for computer-vision implementation depending on interior vs exterior deployment, resolution desired and other factors. Similarly the radiation sensors will be focused on gamma-ray or neutron detection due to the long travel length and ability to penetrate even moderate shielding. There is a significant difference between the vision sensors and radiation sensors in the way the 'source' or signals are generated. A vision sensor needs an external light-source to illuminate the object and then detects the re-emitted illumination (or lack thereof). However, for a radiation detector, the radioactive material is the source itself. The only exception to this is the field of active interrogations where radiation is beamed into a material to entice new/additional radiation emission beyond what the material would emit spontaneously. The aspect of the nuclear material being the source itself means that all other objects in the environment are 'illuminated' or irradiated by the source. Most radiation will readily penetrate regular material, scatter in new directions or be absorbed. Thus if a radiation source is located near a larger object that object will in turn scatter some radiation that was initially emitted in a direction other than the direction of the radiation detector, this can add to the count rate that is observed. The effect of these scatter is a deviation from the traditional distance dependence of the radiation signal and is a key challenge that needs a combined system calibration solution and algorithms. Thus both an algebraic approach as well as a statistical approach have been developed and independently evaluated to investigate the sensitivity to this deviation from the simplified radiation fall-off as a function of distance. The resulting calibrated system algorithms are used and demonstrated in various laboratory scenarios, and later in realistic tracking scenarios. The selection and testing of radiological and computer-vision sensors for the additional specific scenarios will be the subject of ongoing and future work. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Breakup dynamics in a pressure-swirl injector for urea-water solution applications: A computational study

The co-optimization of in-cylinder combustion and after-treatment technology has become a major aspect in engine design and development, with the goal of meeting the increasingly restrictive emission regulations in the transportation industry. Selective Catalytic Reduction is a robust technology to control the emission of NO x , and the injection of urea in water solution is the exhaust tailpipe is a key aspect of its operation. The proposed work uses high-fidelity Computational Fluid Dynamics to characterize the atomization dynamics of the liquid jet in relevant cross-flow conditions. The study focuses on a commercial low-pressure (9 bar) pressure-swirl injector which is characterized in its internal geometry through high-resolution X-ray micro-computational tomography. The internal two-phase flow has been modeled according to the volume-of-fluid approach in a large eddy simulation framework and validated against near-nozzle X-ray radiography measurement. Moreover, characterizing the breakup dynamics for the swirling hollow cone formation, and assessing the influence of the cross-flow in the breakup dynamics was completed. The results have been reported proposing Re-Oh maps and probability density functions of the spray kinematics. Higher cross-flow momentum generates an increase in the jet intact length and a reduction of the liquid droplet diameters. The axial momentum of the jet is affected by the cross-flow already in the near-nozzle region, determining a relevant deviation of the spray velocities. In conclusion, this work aims to inform the initialization of Eulerian-Lagrangian spray models through the assignment of droplet kinematics and static one-way coupling between volume-of-fluid results and Lagrangian spray parcels, to be used for system-size domain simulations.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Quantifying spatiotemporal variability in occupant exposure to an indoor airborne contaminant with an uncertain source location

Well-mixed zone models are often employed to compute indoor air quality and occupant exposures. While effective, a potential downside to assuming instantaneous, perfect mixing is underpredicting exposures to high intermittent concentrations within a room. When such cases are of concern, more spatially resolved models, like computational-fluid dynamics methods, are used for some or all of the zones. But, these models have higher computational costs and require more input information. A preferred compromise would be to continue with a multi-zone modeling approach for all rooms, but with a better assessment of the spatial variability within a room. Here to do so, we present a quantitative method for estimating a room's spatiotemporal variability, based on influential room parameters. Our proposed method disaggregates variability into the variability in a room's average concentration, and the spatial variability within the room relative to that average. This enables a detailed assessment of how variability in particular room parameters impacts the uncertain occupant exposures. To demonstrate the utility of this method, we simulate contaminant dispersion for a variety of possible source locations. We compute breathing-zone exposure during the releasing (source is active) and decaying (source is removed) periods. Using CFD methods, we found after a 30 minutes release the average standard deviation in the spatial distribution of exposure was approximately 28% of the source average exposure, whereas variability in the different average exposures was lower, only 10% of the total average. We also find that although uncertainty in the source location leads to variability in the average magnitude of transient exposure, it does not have a particularly large influence on the spatial distribution during the decaying period, or on the average contaminant removal rate. By systematically characterizing a room's average concentration, its variability, and the spatial variability within the room important insights can be gained as to how much uncertainty is introduced into occupant exposure predictions by assuming a uniform in-room contaminant concentration. We discuss how the results of these characterizations can improve our understanding of the uncertainty in occupant exposures relative to well-mixed models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies

Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Size effect on order-disorder transition kinetics of FePt nanoparticles

The kinetics of order-disorder transition of FePt nanoparticles during high temperature annealing is theoretically investigated. A model is developed to address the influence of large surface to volume ratio of nanoparticles on both the thermodynamic and kinetic aspect of the ordering process; specifically, the nucleation and growth of L1{sub 0} ordered domain within disordered nanoparticles. The size- and shape-dependence of transition kinetics are quantitatively addressed by a revised Johnson-Mehl-Avrami equation that included corrections for deviations caused by the domination of surface nucleation in nanoscale systems and the non-negligible size of the ordered nuclei. Calculation results based on the model suggested that smaller nanoparticles are kinetically more active but thermodynamically less transformable. The major obstacle in obtaining completely ordered nanoparticles is the elimination of antiphase boundaries. The results also quantitatively confirmed the existence of a size-limit in ordering, beyond which, inducing order-disorder transitions through annealing is impossible. A good agreement is observed between theory, experiment, and computer simulation results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Non-equilibrium Green's functions study of discrete dopants variability on an ultra-scaled FinFET

In this paper, we study the effect of random discrete dopants on the performance of a 6.6 nm channel length silicon FinFET. The discrete dopants have been distributed randomly in the source/drain region of the device. Due to the small dimensions of the FinFET, a quantum transport formalism based on the non-equilibrium Green's functions has been deployed. The transfer characteristics for several devices that differ in location and number of dopants have been calculated. Our results demonstrate that discrete dopants modify the effective channel length and the height of the source/drain barrier, consequently changing the channel control of the charge. This effect becomes more significant at high drain bias. As a consequence, there is a strong effect on the variability of the on-current, off-current, sub-threshold slope, and threshold voltage. Finally, we have also calculated the mean and standard deviation of these parameters to quantify their variability. The obtained results show that the variability at high drain bias is 1.75 larger than at low drain bias. However, the variability of the on-current, off-current, and sub-threshold slope remains independent of the drain bias. In addition, we have found that a large source to drain current by tunnelling current occurs at low gate bias.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Observation of $t\bar{t}$ Production in Pb+Pb Collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ATLAS Detector

Top-quark pair production is observed in lead–lead (Pb+Pb) collisions at $\sqrt{s_{NN}}$ = 5.02 TeV at the Large Hadron Collider with the ATLAS detector. The data sample was recorded in 2015 and 2018, amounting to an integrated luminosity of 1.9 nb −1 . Events with exactly one electron and one muon and at least two jets are selected. Top-quark pair production is measured with an observed (expected) significance of 5.0 (4.1) standard deviations. The measured top-quark pair production cross section is 𝜎 𝑡⁢$\tilde{i}$ = 3.6⁢$^{+1.0}_{−0.9}$⁢(stat)⁢ $^{+0.8}_{−0.5}$⁢(syst) μ⁢b, with a total relative uncertainty of 31%, and is consistent with theoretical predictions using a range of different nuclear parton distribution functions. The observation of this process consolidates the evidence of the existence of all quark flavors in the preequilibrium stage of the quark-gluon plasma at very high energy densities, similar to the conditions present in the early Universe.

Quark-gluon plasma↗

DOE OSTI2014

Assessment of interpatient heterogeneity in tumor radiosensitivity for nonsmall cell lung cancer using tumor-volume variation data

Purpose: In our previous work, the authors showed that a distribution of cell surviving fractionsS{sub 2} in a heterogeneous group of patients could be derived from tumor-volume variation curves during radiotherapy for head and neck cancer. In this research study, the authors show that this algorithm can be applied to other tumors, specifically in nonsmall cell lung cancer. This new application includes larger patient volumes and includes comparison of data sets obtained at independent institutions. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage computed tomography. Statistical distributions of cell surviving fractionsS{sub 2} and clearance half-lives of lethally damaged cells T{sub 1/2} have been reconstructed in each patient group by using a version of the two-level cell population model of tumor response and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Nonsmall cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractionsS{sub 2} for nonsmall cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S{sub 2} reconstructed from tumor volume variation agree with the PDF measured in vitro. Conclusions: The data obtained in this work, when taken together with the data obtained previously for head and neck cancer, suggests that the cell surviving fractionsS{sub 2} can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Compensation of Axis Errors of Azimuth and Zenith Moving Concentrators in Programmable Solar-Tracking Systems

The solar-energy industry is currently concerned with improving software systems of sun-tracking concentrators. It is a feature of programmable tracking that there is no feedback from the tracked object, unlike in the case of optical tracking. In this regard, the accuracy of programmable tracking is affected by a large number of factors—in particular, axis-alignment errors. An error-checking algorithm is considered for the azimuth and zenith concentrator axes in programmable sun tracking. Effects of these errors on the accuracy of programmable tracking are assessed. It is shown that zenith axis errors have the same amount of influence as the vertical deviation of the azimuth axis, primarily affecting the azimuth angle, while its influence on the solar elevation can be neglected. The cumulative effect of axial errors is most noticeable when they have the same signs and lie in the same plane.

14 SOLAR ENERGY↗

DOE OSTI2017

Galactic Latitude Dependence of Near-infrared Diffuse Galactic Light: Thermal Emission or Scattered Light?

Near-infrared (IR) diffuse Galactic light (DGL) consists of scattered light and thermal emission from interstellar dust grains illuminated by the interstellar radiation field (ISRF). At 1.25 and 2.2 μm, a recent observational study shows that intensity ratios of the DGL to interstellar 100 μm dust emission steeply decrease toward high Galactic latitudes (b). In this paper, we investigate the origin(s) of the b-dependence on the basis of models of thermal emission and scattered light. Combining a thermal emission model with the regional variation of the polycyclic aromatic hydrocarbon abundance observed with Planck, we show that the contribution of the near-IR thermal emission component to the observed DGL is lower than ∼20%. We also examine the b-dependence of the scattered light, assuming a plane–parallel Galaxy with smooth distributions of the ISRF and dust density along the vertical direction, and assuming a scattering phase function according to a recently developed model of interstellar dust. We normalize the scattered light intensity to the 100 μm intensity corrected for deviation from the cosecant-b law according to the Planck observation. As the result, the present model that considers the b-dependence of dust and the ISRF properties can account for the observed b-dependence of the near-IR DGL. However, the uncertainty in the correction for the 100 μm emission is large, and other normalizing quantities may be appropriate for a more robust analysis of the DGL.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Chemical speciation of U, Fe, and Pu in melt glass from nuclear weapons testing

Nuclear weapons testing generates large volumes of glassy materials that influence the transport of dispersed actinides in the environment and may carry information on the composition of the detonated device. We determine the oxidation state of U and Fe (which is known to buffer the oxidation state of actinide elements and to affect the redox state of groundwater) in samples of melt glass collected from three U.S. nuclear weapons tests. For selected samples, we also determine the coordination geometry of U and Fe, and we report the oxidation state of Pu from one melt glass sample. We find significant variations among the melt glass samples and, in particular, find a clear deviation in one sample from the expected buffering effect of Fe(II)/Fe(III) on the oxidation state of uranium. In the first direct measurement of Pu oxidation state in a nuclear test melt glass, we obtain a result consistent with existing literature that proposes Pu is primarily present as Pu(IV) in post-detonation material. In addition, our measurements imply that highly mobile U(VI) may be produced in significant quantities when melt glass is quenched rapidly following a nuclear detonation, though these products may remain immobile in the vitrified matrices. The observed differences in chemical state among the three samples show that redox conditions can vary dramatically across different nuclear test conditions. The local soil composition, associated device materials, and the rate of quenching are all likely to affect the final redox state of the glass. The resulting variations in glass chemistry are significant for understanding and interpreting debris chemistry and the later environmental mobility of dispersed material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Measurement of the Higgs boson width and evidence of its off-shell contributions to ZZ production

Since the discovery of the Higgs boson in 2012, detailed studies of its properties have been ongoing. Besides its mass, its width - related to its lifetime - is an important parameter. One way to determine this quantity is by measuring its off-shell production, where the Higgs boson mass is far away from its nominal value, and relating it to its on-shell production, where the mass is close to the nominal value. Here, we report evidence for such off-shell contributions to the production cross section of two Z bosons with data from the CMS experiment at the CERN Large Hadron Collider. We constrain the total rate of the off-shell Higgs boson contribution beyond the Z boson pair production threshold, relative to its standard model expectation, to the interval [0.0061, 2.0] at 95% confidence level. The scenario with no off-shell contribution is excluded at a p-value of 0.0003 (3.6 standard deviations). We measure the width of the Higgs boson as $\Gamma_{\mathrm{H}}$ = 3.2 $_{-1.7}^{+2.4}$ MeV, in agreement with the standard model expectation of 4.1 MeV. In addition, we set constraints on anomalous Higgs boson couplings to W and Z boson pairs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

An Assessment of Some Design Constraints on Heat Production of a 3D Conceptual EGS Model Using an Open-Source Geothermal Reservoir Simulation Code

Performance of heat production process over a 30-year period is assessed in a conceptual EGS model with a geothermal gradient of 65K per km depth in the reservoir. Water is circulated through a pair of parallel wells connected by a set of single large wing fractures. The results indicate that the desirable output electric power rate and lifespan could be obtained under suitable material properties and system parameters. A sensitivity analysis on some design constraints and operation parameters indicates that 1) the fracture horizontal spacing has profound effect on the long-term performance of heat production, 2) the downward deviation angle for the parallel doublet wells may help overcome the difficulty of vertical drilling to reach a favorable production temperature, and 3) the thermal energy production rate and lifespan has close dependence on water mass flow rate. The results also indicate that the heat production can be improved when the horizontal fracture spacing, well deviation angle, and production flow rate are under reasonable conditions. To conduct the reservoir modeling and simulations, an open-source, finite element based, fully implicit, fully coupled hydrothermal code, namely FALCON, has been developed and used in this work. Compared with most other existing codes that are either closed-source or commercially available in this area, this new open-source code has demonstrated a code development strategy that aims to provide an unparalleled easiness for user-customization and multi-physics coupling. Test results have shown that the FALCON code is able to complete the long-term tests efficiently and accurately, thanks to the state-of-the-art nonlinear and linear solver algorithms implemented in the code.

enhanced geothermal system↗

DOE OSTI2017

Falling Outer Rotation Curves of Star-forming Galaxies at 0.6 ≲ z ≲ 2.6 Probed with KMOS{sup 3D} and SINS/zC-SINF

We exploit the deep, resolved, Hα kinematic data from the KMOS{sup 3D} and SINS/zC-SINF surveys to examine the largely unexplored outer-disk kinematics of star-forming galaxies (SFGs), out to the peak of cosmic star formation. Our sample contains 101 SFGs, representative of the more massive (9.3≲logM{sub ∗}/M{sub ⊙}≲11.5) main sequence population at 0.6 ≤ z ≤ 2.6. Through a novel stacking approach, we are able to constrain a representative rotation curve extending out to ∼4 effective radii. This average rotation curve exhibits a significant drop in rotation velocity beyond the turnover, with a slope of ΔV/ΔR=−0.26{sub −0.09}{sup +0.10} in units of normalized coordinates V/V {sub max} and R/R {sub turn}. This result confirms that the fall-off seen in some individual galaxies is a common feature of our sample of high-z disks. The outer fall-off strikingly deviates from the flat or mildly rising rotation curves of local spiral galaxies that have similar masses. Through a comparison with models that include baryons and dark matter, we demonstrate that the falling stacked rotation curve is consistent with a high mass fraction of baryons, relative to the total dark matter halo (m {sub d} ≳ 0.05), in combination with a sizeable level of pressure support in the outer disk. These findings agree with recent studies demonstrating that high-z star-forming disks are strongly baryon-dominated within the disk scale, and furthermore suggest that pressure gradients caused by large, turbulent gas motions are present even in their outer disks. These results are largely independent of our model assumptions, such as the presence of stellar bulges, the effect of adiabatic contraction, and variations in halo concentration.

79 ASTRONOMY AND ASTROPHYSICS↗