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Velocity distribution measurement of excited potassium bromide formed in reactive collision between crossed beams of K and HBr as function of scattering angle for selected K velocity
In this study, the spatial structure of cumulus cloud populations is investigated using three-dimensional snapshots from large-domain LES experiments. The aim is to understand and quantify the internal variability in cloud size distributions due to subsampling effects and spatial organization. A set of idealized shallow cumulus cases is selected with varying degrees of spatial organization, including a slowly organizing marine precipitating case and five more quickly organizing diurnal cases over land. A subdomain analysis is applied, yielding cloud number distributions at sample sizes ranging from severely undersampled to nearly complete. A strong power-law scaling is found in the relation between cloud number variability and subdomain size, reflecting an inverse linear relation. Scaling subdomain size by cloud size yields a data collapse across time points and cases, highlighting the role played by cloud spacing in controlling the stochastic variability. Spatial organization acts on top of this baseline model by increasing the maximum cloud size and by enhancing the variability in the number of smallest clouds. This reflects that the smaller clouds start to live on top of larger-scale thermodynamic structures, such as cold pools, which favor or inhibit their formation. Compositing all continental cumulus cases suggests the existence of a prototype diurnal time dependence in the spatial organization. A simple stochastic expression for cloud number variability is proposed that is formulated in terms of two dimensionless groups, which allows objective estimation of the degree of spatial organization in simulated and observed cumulus cloud populations.
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes of computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.
In an aspect, a method of synthesizing a graft copolymer comprises the steps of: copolymerizing a first macromonomer and a first reactive diluent; wherein said first macromonomer comprises a first backbone precursor directly or indirectly covalently linked to a first polymer side chain group; wherein said reactive diluent is provided in the presence of the first macromonomer at an amount selected so as to result in formation said graft copolymer having a first backbone incorporating said diluent and said first macromonomer in a first polymer block characterized by a preselected first graft density or a preselected first graft distribution of said first macromonomer. In some embodiments of this aspect, said preselected first graft density is any value selected from the range of 0.05 to 0.75. In some methods, the composition and amount of said diluent is selected to provide both a first preselected first graft density and a first preselected first graft distribution.
We provide a prescription called ThickBrick to train optimal machine-learning-based event selectors and categorizers that maximize the statistical significance of a potential signal excess in high energy physics (HEP) experiments, as quantified by any of six different performance measures. For analyses where the signal search is performed in the distribution of some event variables, our prescription ensures that only the information complementary to those event variables is used in event selection and categorization. This eliminates a major misalignment with the physics goals of the analysis (maximizing the significance of an excess) that exists in the training of typical ML-based event selectors and categorizers. In addition, this decorrelation of event selectors from the relevant event variables prevents the background distribution from becoming peaked in the signal region as a result of event selection, thereby ameliorating the challenges imposed on signal searches by systematic uncertainties. Our event selectors (categorizers) use the output of machine-learning-based classifiers as input and apply optimal selection cutoffs (categorization thresholds) that are functions of the event variables being analyzed, as opposed to flat cutoffs (thresholds). These optimal cutoffs and thresholds are learned iteratively, using a novel approach with connections to Lloyd’s k-means clustering algorithm. We provide a public, Python implementation of our prescription, also called ThickBrick, along with usage examples.
The use of a Monte Carlo model for generating sample directional reflectance data for two simplified target canopies at two different solar positions is reported. Successive iterations through the model permit the calculation of a mean vector and covariance matrix for canopy reflectance for varied sensor view angles. These data may then be used to calculate the divergence between the target distributions for various wavelength combinations and for these view angles. Results of a feature selection analysis indicate that different sets of wavelengths are optimum for target discrimination depending on sensor view angle and that the targets may be more easily discriminated for some scan angles than others. The time-varying behavior of these results is also pointed out.
MFI zeolites contain ten-membered ring channels (∼0.55 nm diameter) that intersect to form larger voids (∼0.70 nm diameter). The distribution of framework Al sites dictates the void environments that confine active H + sites. MFI synthesized with pentaerythritol (PET) and Na + as structure-directing agents are interrogated using kinetically controlled toluene methylation rates and xylene isomer selectivities. High para-xylene selectivity and low toluene methylation rates indicate that MFI-PET samples contain H + sites predominantly in smaller channels. As-synthesized samples contain more framework Al than Na + , indicating that some charge compensation is provided by protonated PET-solvent complexes that bias Al siting towards these smaller channels.
Catalytic hydrodeoxygenation (HDO) of phenolics is a necessary step for upgrading bio-oils to transportation fuels. Bimetallic catalysts offer the potential of increased activities and selectivities for desired products. Adding non-metallic elements, such as phosphorous, allows for charge distribution between the metal and nonmetal atoms, which improves Lewis acid character of catalytic surfaces. This work utilizes experimental and density functional theory (DFT) based calculations to identify potential C–O bond cleavage pathways and product selectivities for HDO reactions on FeMoP, RuMoP, and NiMoP catalysts. Our work demonstrates that FeMoP catalyst favors direct deoxygenation pathway due to a lower activation energy barrier for C–O bond cleavage whereas RuMoP and NiMoP catalysts promote ring hydrogenation first, followed by the cleavage of C–O bond. The Bader charge analysis indicates that for these catalytic systems Moδ+ site bears a large positive charge which acts as a Lewis acid site for HDO reactions. Altogether, we find that trends in the experimental product selectivities are in good agreement with that predicted with DFT calculations.
The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment’s run. More than 20 terabytes of data must be stored every night, and annual campaigns to reprocess the entire dataset since the beginning of the survey will be conducted over ten years. The Production and Distributed Analysis (PanDA) system was evaluated by the Rubin Observatory Data Management team and selected to serve the Observatory’s needs due to its demonstrated scalability and flexibility over the years, for its Directed Acyclic Graph (DAG) support, its support for multi-site processing, and its highly scalable complex workflows via the intelligent Data Delivery Service (iDDS). PanDA is also being evaluated for prompt processing where data must be processed within 60 seconds after image capture. This paper will briefly describe the Rubin Data Management system and its Data Facilities (DFs). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA.
From its location on the subtropics-midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes, and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets to deep convective systems. This project combined three types of data sets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three data sets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high-pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for post-frontal environments and northwesterly flows. An evaluation of CMIP5 climate model cloud regimes over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that carefully selected case studies can be related through regime analysis to climatological cloud distributions, and a methodology is suggested utilizing process-resolving model simulations of individual cases to better understand cloud-dynamics interactions and attempt to explain and correct climate model cloud deficiencies.
An experimental study was made to obtain quantitative information on heat transfer, flow, and pressure distribution in a branched duct test section that had several significant features of an internal cooling passage of a turbine blade. The objective of this study was to generate a set of experimental data that could be used for validation of computer codes that would be used to model internal cooling. Surface heat transfer coefficients and entrance flow conditions were measured at nominal entrance Reynolds numbers of 45,000, 335,000, and 726,000. Heat transfer data were obtained by using a steady-state technique in which an Inconel heater sheet is attached to the surface and coated with liquid crystals. Visual and quantitative flow-field data from particle image velocimetry measurements for a plane at midchannel height for a Reynolds number of 45,000 were also obtained. The flow was seeded with polystyrene particles and illuminated by a laser light sheet. Pressure distribution measurements were made both on the surface with discrete holes and in the flow field with a total pressure probe. The flow-field measurements yielded flow-field velocities at selected locations. A relatively new method, pressure sensitive paint, was also used to measure surface pressure distribution. The pressure paint data obtained at Reynolds numbers of 335,000 and 726,000 compared well with the more standard method of measuring pressures by using discrete holes.
A redundant frequency and time distribution system provides a multiplicity of isolated outputs, all of which are derived from three atomic frequency standards. The distribution system monitors input parameters of the signals coming from the Cesium Standards and selects one to be the primary standard, phase locks an internal oscillator which has excellent aging characteristics in the open loop mode and acts as a filter to provide phase noise improvement, and generates 1 megahertz and 100 kHz by direct synthesis. Additionally, the system distributes RF and timing signals consisting of 5 MHz, 1 MHz, 100 kHz, BCD Time-of-Day, 1 pps and 1 ppm.
Over the previous year the Space Station Freedom (SSF) Program (SSFP) ground data distribution system has become independent of a number of data systems that were to have been provided by other National Aeronautics and Space Administration (NASA) programs. Consequently, the SSFP has outlined the basic architecture of a new data system dedicated to supporting SSF requirements. This has been accomplished through a complete redesign of the ground network and a reallocation of selected functions. There are a number of aspects of the new ground data distribution system that are unique among NASA programs. These considerations make SSF ground data distribution one of the most extensive and complex data management challenges encountered in the arena of Space Operations. A description of this system comprises the main focus of the paper.
We present an atlas of the spectral energy distributions (SEDs) of normal, nonblazar, quasars over the whole available range (radio to 10 keV X-rays) of the electromagnetic spectrum. The primary (UVSX) sample includes 47 quasars for which the spectral energy distributions include X-ray spectral indices and UV data. Of these, 29 are radio quiet, and 18 are radio loud. The SEDs are presented both in figures and in tabular form, with additional tabular material published on CD-ROM. Previously unpublished observational data for a second set of quasars excluded from the primary sample are also tabulated. The effects of host galaxy starlight contamination and foreground extinction on the UVSX sample are considered and the sample is used to investigate the range of SED properties. Of course, the properties we derive are influenced strongly by the selection effects induced by quasar discovery techniques. We derive the mean energy distribution (MED) for radio-loud and radio-quiet objects and present the bolometric corrections derived from it. We note, however, that the dispersion about this mean is large (approximately one decade for both the infrared and ultraviolet components when the MED is normalized at the near-infrared inflection). At least part of the dispersion in the ultraviolet may be due to time variability, but this is unlikely to be important in the infrared. The existence of such a large dispersion indicates that the MED reflects only some of the properties of quasars and so should be used only with caution.
In this study, we investigated the correlation between 2-dimensional (2D) and 3D gamma analysis using the new PTW OCTAVIUS 4D system for various parameters. For this study, we selected 150 clinically approved volumetric-modulated arc therapy (VMAT) plans of head and neck (50), thoracic (esophagus) (50), and pelvic (cervix) (50) sites. Individual verification plans were created and delivered to the OCTAVIUS 4D phantom. Measured and calculated dose distributions were compared using the 2D and 3D gamma analysis by global (maximum), local and selected (isocenter) dose methods. The average gamma passing rate for 2D global gamma analysis in coronal and sagittal plane was 94.81% ± 2.12% and 95.19% ± 1.76%, respectively, for commonly used 3-mm/3% criteria with 10% low-dose threshold. Correspondingly, for the same criteria, the average gamma passing rate for 3D planar global gamma analysis was 95.90% ± 1.57% and 95.61% ± 1.65%. The volumetric 3D gamma passing rate for 3-mm/3% (10% low-dose threshold) global gamma was 96.49% ± 1.49%. Applying stringent gamma criteria resulted in higher differences between 2D planar and 3D planar gamma analysis across all the global, local, and selected dose gamma evaluation methods. The average gamma passing rate for volumetric 3D gamma analysis was 1.49%, 1.36%, and 2.16% higher when compared with 2D planar analyses (coronal and sagittal combined average) for 3 mm/3% global, local, and selected dose gamma analysis, respectively. On the basis of the wide range of analysis and correlation study, we conclude that there is no assured correlation or notable pattern that could provide relation between planar 2D and volumetric 3D gamma analysis. Owing to higher passing rates, higher action limits can be set while performing 3D quality assurance. Site-wise action limits may be considered for patient-specific QA in VMAT.
The anomalous mole fraction effect of L-type calcium channels is analyzed using a Fermi like distribution with the experimental data of Almers and McCleskey [J. Physiol. 353, 585 (1984)] and the atomic resolution model of Lipkind and Fozzard [Biochemistry 40, 6786 (2001)] of the selectivity filter of the channel. Much of the analysis is algebraic, independent of differential equations. The Fermi distribution is derived from the configuration entropy of ions and water molecules with different sizes, different valences, and interstitial voids between particles. It allows us to calculate potentials and distances (between the binding ion and the oxygen ions of the glutamate side chains) directly from the experimental data using algebraic formulas. The spatial resolution of these results is comparable with those of molecular models, but of course the accuracy is no better than that implied by the experimental data. The glutamate side chains in our model are flexible enough to accommodate different types of binding ions in different bath conditions. The binding curves of Na{sup +} and Ca{sup 2+} for [CaCl{sub 2}] ranging from 10{sup −8} to 10{sup −2} M with a fixed 32 mM background [NaCl] are shown to agree with published Monte Carlo simulations. The Poisson-Fermi differential equation—that includes both steric and correlation effects—is then used to obtain the spatial profiles of energy, concentration, and dielectric coefficient from the solvent region to the filter. The energy profiles of ions are shown to depend sensitively on the steric energy that is not taken into account in the classical rate theory. We improve the rate theory by introducing a steric energy that lumps the effects of excluded volumes of all ions and water molecules and empty spaces between particles created by Lennard-Jones type and electrostatic forces. We show that the energy landscape varies significantly with bath concentrations. The energy landscape is not constant.
A large stock of multifamily buildings in the Northeast and Midwest uses hot water or steam for space heating. Typically, residents do not pay for heat directly (i.e., heating fuel serves a central plant and use is not submetered). Losses from these systems are typically high, and a significant number of apartments are overheated much of the time. This is often evidenced by open windows on winter days. Controls and distribution are often faulty, and improving them can be more cost effective than replacing boilers. Thermostatic radiator valves (TRVs), which have been in use for many decades, are one potential strategy to combat this problem. They are commonly used in Europe and in other markets such as commercial buildings, but have not been widely accepted by the residential retrofit market in the northeastern United States. Anecdotal evidence suggests that heating systems engineers and contractors have a variety of opinions about their effectiveness, illustrating a lack of consensus on this potentially important energy efficiency measure. A review of the limited available literature revealed that, in one study, heating fuel savings as high as 15% was achieved through TRV retrofits. In this project, the U.S. Department of Energy Building America team, Advanced Residential Integrated Energy Solutions, sought to better understand the current usage of TRVs by key market players in steam and hot water heating and to conduct limited experiments on the effectiveness of new and old TRVs as a means of controlling space temperatures and reducing heating fuel consumption. The project included a survey of industry professionals, a field experiment comparing old and new TRVs, and cost-benefit modeling analysis using BEopt (Building Energy Optimization software). Radiator and apartment space temperature data were collected and analyzed for two similar apartment units in a building that underwent a one-pipe steam TRV retrofit. Space temperature comparisons were made across the pre- and post-TRV installation heating periods and between rooms equipped with old or new TRVs in an attempt to show the comparative effectiveness of each vintage of TRV. Analyses of the heating fuel utility bills before and after the building-wide TRV installation were conducted to quantify potential savings. The results of the field experiment and utility bill analysis did not show energy savings at either the unit or the building-wide level. The results provided inconclusive answers to the original study questions but provided valuable insight into common steam system imbalance and resident behavior issues that are critical to address in conjunction with TRV retrofits. Specific issues identified included steam distribution imbalance, possible TRV sensor location issues, a persistent window-opening habit, and a failure to optimize the boiler control set points as part of the TRV retrofit. The lack of heating fuel savings underscored the need to include whole steam system commissioning alongside or as a prerequisite to TRVs. Failed air vents and uneven steam main venting are critical to address either in conjunction with or before a TRV installation. Monitoring existing space temperatures before a retrofit strategy is chosen would allow the consultant and building owner to better assess the potential benefits of a whole-building TRV retrofit, selective installation of TRVs in some units, or simply balancing the steam distribution venting. Further gaps in the understanding of underlying processes that allow TRVs to function effectively were also identified and are presented as opportunities for future research.
Gamma-ray bursts (GRBs) are fascinating events due to their panchromatic nature. We study optical plateaus in GRB afterglows via an extended search into archival data. We comprehensively analyze all published GRBs with known redshifts and optical plateaus observed by many ground-based telescopes (e.g., Subaru Telescope, RATIR) around the world and several space-based observatories such as the Neil Gehrels Swift Observatory. We fit 500 optical light curves, showing the existence of the plateau in 179 cases. This sample is 75% larger than the previous one, and it is the largest compilation so far of optical plateaus. We discover the 3D fundamental plane relation at optical wavelengths using this sample. This correlation is between the rest-frame time at the end of the plateau emission, ${T}_{\mathrm{opt}}^{* }$, its optical luminosity, L opt , and the peak in the optical prompt emission, L peak,opt , thus resembling the three-dimensional (3D) X-ray fundamental plane (the so-called 3D Dainotti relation). We correct our sample for redshift evolution and selection effects, discovering that this correlation is indeed intrinsic to GRB physics. We investigate the rest-frame end-time distributions in X-rays and optical (${T}_{\mathrm{opt}}^{* }$, ${T}_{{\rm{X}}}^{* }$), and conclude that the plateau is achromatic only when selection biases are not considered. We also investigate if the 3D optical correlation may be a new discriminant between optical GRB classes and find that there is no significant separation between the classes compared to the Gold sample plane after correcting for evolution.