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At least 1,801 records · Page 100

Effect of Terrestrial and Marine Organic Aerosol on Regional and Global Climate: Model Development, Application, and Verification with Satellite Data

In this DOE project the improvements to parameterization of marine primary organic matter (POM) emissions, hygroscopic properties of marine POM, marine isoprene derived secondary organic aerosol (SOA) emissions, surfactant effects, new cloud droplet activation parameterization have been implemented into Community Atmosphere Model (CAM 5.0), with a seven mode aerosol module from the Pacific Northwest National Laboratory (PNNL)'s Modal Aerosol Model (MAM7). The effects of marine aerosols derived from sea spray and ocean emitted biogenic volatile organic compounds (BVOCs) on microphysical properties of clouds were explored by conducting 10 year CAM5.0-MAM7 model simulations at a grid resolution 1.9° by 2.5° with 30 vertical layers. Model-predicted relationship between ocean physical and biological systems and the abundance of CCN in remote marine atmosphere was compared to data from the A-Train satellites (MODIS, CALIPSO, AMSR-E). Model simulations show that on average, primary and secondary organic aerosol emissions from the ocean can yield up to 20% increase in Cloud Condensation Nuclei (CCN) at 0.2% Supersaturation, and up to 5% increases in droplet number concentration of global maritime shallow clouds. Marine organics were treated as internally or externally mixed with sea salt. Changes associated with cloud properties reduced (absolute value) the model-predicted short wave cloud forcing from -1.35 Wm -2 to -0.25 Wm -2 . By using different emission scenarios, and droplet activation parameterizations, this study suggests that addition of marine primary aerosols and biologically generated reactive gases makes an important difference in radiative forcing assessments. All baseline and sensitivity simulations for 2001 and 2050 using global-through-urban WRF/Chem (GU-WRF) were completed. The main objective of these simulations was to evaluate the capability of GU-WRF for an accurate representation of the global atmosphere by exploring the most accurate configuration of physics options in GWRF for global scale modeling in 2001 at a horizontal grid resolution of 1° x 1°. GU-WRF model output was evaluated using observational datasets from a variety of sources including surface based observations (NCDC and BSRN), model reanalysis (NCEP/ NCAR Reanalysis and CMAP), and remotely-sensed data (TRMM) to evaluate the ability of GU-WRF to simulate atmospheric variables at the surface as well as aloft. Explicit treatment of nanoparticles produced from new particle formation in GU-WRF/Chem-MADRID was achieved by expanding particle size sections from 8 to 12 to cover particles with the size range of 1.16 nm to 11.6m. Simulations with two different nucleation parameterizations were conducted for August 2002 over a global domain at a 4º by 5º horizontal resolution. The results are evaluated against field measurement data from the 2002 Aerosol Nucleation and Real Time Characterization Experiment (ANARChE) in Atlanta, Georgia, as well as satellite and reanalysis data. We have also explored the relationship between clean marine aerosol optical properties and ocean surface wind speed using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses were carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. We show that for very low (less than 4 m s -1 ) and very high (more than 12 m s -1 ) wind speed conditions the mean CALIPSO-derived aerosol optical depth (AOD) has little dependency on the surface wind speed. For an intermediate (between 4 and 12 m s -1 ) marine AOD was linearly correlated with the surface wind speed values, with a slope of 0.0062 s m -1 . Results of our study suggest that considerable improvements to both optical properties of marine aerosols and their production mechanisms can be achieved by discriminating clean marine aerosols (or sea salt particles) from all other types of aerosols present over the ocean.

54 ENVIRONMENTAL SCIENCES↗

SAINT: A combined simulation language for modeling man-machine systems

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

Seifert, D. J.↗

The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO)

NASA's Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to leverage Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) to improve asset coordination and overall emergency response. One application of STEReO is wildfire response, which is the focus of this research. In order to implement the operations described in the STEReO project, these additions must have tangible benefits and proven safety. To this end, the System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO) project constructs a simulation model, developed through the Python modeling and resiliency analysis package fmdtools. The model describes wildfire response operations, including current operational concepts and emerging concepts utilizing UAS as described in STEReO. While previous simulation models focus primarily on fire propagation with some models including emergency response intervention, SMART-STEReO evaluates the system performance and resilience benefits gained by the addition of UAS and UTM. Due to the novelty and complexity of the model, initial model verification and validation efforts are conducted and a detailed description of the model is provided. Preliminary results from experimental analysis on the SMARt-STEReO model indicate that when compared to current operations, the addition of UAS in wildfire operations results in improved response efforts, in terms of fewer acres burned, as well as improved system resilience in response to a given fault.

Sequoia Andrade↗

Electron transport in unipolar InGaN/GaN multiple quantum well structures grown by NH{sub 3} molecular beam epitaxy

Unipolar-light emitting diode like structures were grown by NH{sub 3} molecular beam epitaxy on c plane (0001) GaN on sapphire templates. Studies were performed to experimentally examine the effect of random alloy fluctuations on electron transport through quantum well active regions. These unipolar structures served as a test vehicle to test our 2D model of the effect of compositional fluctuations on polarization-induced barriers. Variables that were systematically studied included varying quantum well number from 0 to 5, well thickness of 1.5 nm, 3 nm, and 4.5 nm, and well compositions of In{sub 0.14}Ga{sub 0.86}N and In{sub 0.19}Ga{sub 0.81}N. Diode-like current voltage behavior was clearly observed due to the polarization-induced conduction band barrier in the quantum well region. Increasing quantum well width and number were shown to have a significant impact on increasing the turn-on voltage of each device. Temperature dependent IV measurements clearly revealed the dominant effect of thermionic behavior for temperatures from room temperature and above. Atom probe tomography was used to directly analyze parameters of the alloy fluctuations in the quantum wells including amplitude and length scale of compositional variation. A drift diffusion Schrödinger Poisson method accounting for two dimensional indium fluctuations (both in the growth direction and within the wells) was used to correctly model the turn-on voltages of the devices as compared to traditional 1D simulation models.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Development and validation of a radial inflow turbine model for simulation of the SNL S-CO 2 split-flow loop

A one-dimensional model for a radial inflow turbine has been developed for super-critical carbon dioxide (S-CO 2 ) Brayton cycle applications. The model accounts for the main phenomena present in the volute, nozzle, and impeller of a single-stage turbine. These phenomena include internal losses due to friction, blade loading, and angle of incidence and parasitic losses due to windage and blade-housing leakage. The model has been added as a component to the G-PASS plant systems code. The model was developed to support the analysis of S-CO 2 cycles in conjunction with small-scale loop experiments. Such loops operate at less than a MWt thermal input. Their size permits components to be reconfigured in new arrangements relatively easily and economically. However, the small thermal input combined with the properties of carbon dioxide lead to turbomachines with impeller diameters of only one to two inches. At these sizes the dominant phenomena differ from those in larger more typical machines. There is almost no treatment in the literature of turbomachines at these sizes. The present work therefore is aimed at developing turbomachine models that support the task of S-CO 2 cycle analysis using small-scale tests. Model predictions were compared against data from an experiment performed for Sandia National Laboratories in the split-flow Brayton cycle loop currently located at Barber-Nichols Inc. The split-flow loop incorporates two turbo-alternator-compressor (TAC) units each incorporating a radial inflow turbine and a radial flow compressor on a common shaft. The predicted thermodynamic conditions at the outlet of the turbine on the main compressor shaft were compared with measured values at different shaft speeds. Two modifications to the original model were needed to better match the experiment data. First, a representation of the heat loss from the volute downstream of the sensed inlet temperature was added. Second, an empirical multiplicative factor was applied to the Euler head and another to the head loss to bring the predicted outlet pressure into better agreement with the experiment. These changes also brought the overall efficiency of the turbine into agreement with values cited by Barber Nichols for small turbines. More generally, the quality of measurement set data can in the future be improved by additional steps taken in the design and operation of the experimental apparatus. First, a thermocouple mounted at the nozzle inlet would provide a better indication of temperature at this key point. Second, heat losses from the turbine should be measured directly. Allowing the impeller to free wheel at inlet conditions and measuring the temperature drop between inlet and outlet would provide a more accurate measure of heat loss. Finally, the enthalpy change during operation is more accurately obtained by measuring the torque on the stator using strain gauges rather than by measuring pressure and temperature at inlet and outlet to infer thermodynamic states.

42 ENGINEERING↗

MODELING AND SIMULATION OF SOLID FLUIDIZATION IN A RESIN COLUMN

The objective of the present work is to model the resin particles within the column during fluidization and sedimentation processes using computation fluid dynamics (CFD) approach. The calculated results will help interpret experimental results, and they will assist in providing guidance on specific details of testing design and establishing a basic understanding of particle’s hydraulic characteristics within the column. The model is benchmarked against the literature data and the test data (2003) conducted at Savannah River Site (SRS). The paper presents the benchmarking results and the modeling predictions of the SRS resin column using the improved literature correlations applicable for liquid-solid granular flow.

42 ENGINEERING↗

An intercomparison of wall fluxes in a turbulent thermal convection chamber: Direct numerical simulations and wall-modeled large-eddy simulations enhanced by machine learning

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall models, a new wall model employing physics-aware neural networks, and a refined grid near the walls. The experiment involves four cases with varying sidewall temperatures. Our results show that LESs capture the main flow features and the trends of mean fluxes. The physics-aware neural networks and refined wall grids can improve the temporally averaged local fluxes when the large-scale circulation has a preferred direction. Even without the local improvement of wall fluxes, the LES flow quantities (temperature and velocities) can still largely match those in DNSs, provided the mean flux largely matches the DNSs. Additionally, DNSs reveal that a variation in corner treatments has minimal impacts on the flow quantities away from corners. Finally, LESs underestimate the mean fluxes of the entire wall due to their inability to resolve corner regions, but their mean flux away from the corner can better match DNS.

54 ENVIRONMENTAL SCIENCES↗

Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: new models and constraints from the eBOSS measurement

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-α forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with 40963 hydrodynamical cells in a 120 Mpc (∼ 81 Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-α forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters A Lyα and n Lyα . While the best-fit Planck ΛCDM model has A Lyα = 8.79 and n Lyα = -2.363, from DR14 eBOSS data we find that A Lyα < 7.6 (95% CI) and n Lyα = -2.369 ± 0.008. The low value of A Lyα , in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman-α forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find A Lyα = 9.8 ± 1.1 in accordance with Planck.

Walther, Michael↗

The use of variograms in remote sensing. I - Scene models and simulated images. II - Real digital images

Theoretical and empirical studies of variograms are presented. The sensitivity of variograms is studied through varyig parameters of scene models both in calculating explicit variograms and in simulating images. It is found that the heights of variograms are related to the proportion of an area covered by objects. It is shown that the range of influence of a variogram is related to the size of the objects in the scene and that the shape of the variogram becomes more rounded as the variance in the size distribution of objects increases. In the second part, empirically calculated variograms from real digital images are used to demonstrate these theoretical findings. These calculated variograms also show the periodicity in ground scenes and reveal anisotropy.

Woodcock, Curtis E.↗

Resin Film Infusion (RFI) Process Modeling for Large Transport Aircraft Wing Structures

This investigation completed the verification of a three-dimensional resin transfer molding/resin film infusion (RTM/RFI) process simulation model. The model incorporates resin flow through an anisotropic carbon fiber preform, cure kinetics of the resin, and heat transfer within the preform/tool assembly. The computer model can predict the flow front location, resin pressure distribution, and thermal profiles in the modeled part. The formulation for the flow model is given using the finite element/control volume (FE/CV) technique based on Darcy's Law of creeping flow through a porous media. The FE/CV technique is a numerically efficient method for finding the flow front location and the fluid pressure. The heat transfer model is based on the three-dimensional, transient heat conduction equation, including heat generation. Boundary conditions include specified temperature and convection. The code was designed with a modular approach so the flow and/or the thermal module may be turned on or off as desired. Both models are solved sequentially in a quasi-steady state fashion. A mesh refinement study was completed on a one-element thick model to determine the recommended size of elements that would result in a converged model for a typical RFI analysis. Guidelines are established for checking the convergence of a model, and the recommended element sizes are listed. Several experiments were conducted and computer simulations of the experiments were run to verify the simulation model. Isothermal, non-reacting flow in a T-stiffened section was simulated to verify the flow module. Predicted infiltration times were within 12-20% of measured times. The predicted pressures were approximately 50% of the measured pressures. A study was performed to attempt to explain the difference in pressures. Non-isothermal experiments with a reactive resin were modeled to verify the thermal module and the resin model. Two panels were manufactured using the RFI process. One was a stepped panel and the other was a panel with two 'T' stiffeners. The difference between the predicted infiltration times and the experimental times was 4% to 23%.

Loos, Alfred C.↗

Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models

Purpose To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)'s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.Methods We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANNs) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.Results The optimal ANN for SimCRC had 4 hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had 1 hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 h for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.Conclusions Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, such as the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating 3 realistic CRC individual-level models using a Bayesian approach.

artificial neural networks↗

A single-column particle-resolved model for simulating the vertical distribution of aerosol mixing state: WRF-PartMC-MOSAIC-SCM v1.0

Abstract. The PartMC-MOSAIC particle-resolved aerosol model was previously developed to predict the aerosol mixing state as it evolves in the atmosphere. However, the modeling framework was limited to a zero-dimensional box model approach without resolving spatial gradients in aerosol concentrations. This paper presents the development of stochastic particle methods to simulate turbulent diffusion and dry deposition of aerosol particles in a vertical column within the planetary boundary layer. The new model, WRF-PartMC-MOSAIC-SCM, resolves the vertical distribution of aerosol mixing state. We verified the new algorithms with analytical solutions for idealized test cases and illustrate the capabilities with results from a 2-day urban scenario that shows the evolution of black carbon mixing state in a vertical column.

54 ENVIRONMENTAL SCIENCES↗

On multidomain multiscale modeling and simulation of a novel partial pressure and temperature swing adsorptive reactor ($\mathrm{PPTSAR}$) with application to the water gas shift reaction

Here in this work, a dynamic, multidomain, multiscale model of a novel Partial Pressure and Temperature Swing Adsorptive Reactor (PPTSAR) Process is developed and simulated for a Water Gas Shift Reaction (WGSR) application. The proposed model couples the reactor wall, catalyst/adsorbent pellet, and fluid mixture domains at their respective scales to comprehensively model mass, momentum, and energy transport phenomena occurring within each domain. The resulting model elucidates the PPTSAR’s start-up, transient, and long-term, periodic, dynamic behavior, during both adsorption/reaction and desorption operating modes. In the WGSR application considered, the use of two PPTSARs is shown to allow continuous operation that delivers CO conversion greater than 95% with simultaneous complete CO 2 capture.

42 ENGINEERING↗

Monthly mean simulation experiments with a course-mesh global atmospheric model

Substitution of observed monthly mean sea-surface temperatures (SSTs) as lower boundary conditions, in place of climatological SSTs, failed to improve the model simulations. While the impact of SST anomalies on the model output is greater at sea level than at upper levels the impact on the monthly mean simulations is not beneficial at any level. Shifts of one and two days in initialization time produced small, but non-trivial, changes in the model-generated monthly mean synoptic fields. No improvements in the mean simulations resulted from the use of either time-averaged initial data or re-initialization with time-averaged early model output. The noise level of the model, as determined from a multiple initial state perturbation experiment, was found to be generally low, but with a noisier response to initial state errors in high latitudes than the tropics.

Spar, J.↗

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models.The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar convexwall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University. The favorable pressure gradient is induced bythe streamwise surface curvature. The DNS results will be compared with experimental measurements and RANS computations for the same flow conditions and wall geometry. The DNS datasets will also be analyzed to provide an improved physical understanding of hypersonic boundary-layer turbulence subject to mechanical nonequilibrium, including the validity of Morkovin’s hypothesis and the various available compressibility transformations, as well as to obtain turbulence statistics that are relevant to RANS modeling, including the distribution ofeddy viscosity, the budgets of turbulent kinetic energy and Reynolds stresses, and the velocity-temperature correlations. The RANS predictions will be obtained by using both the commonly used one- and two-equation models that assume a constant turbulent Prandtl number and an algebraic, variable Prandtl number model for the turbulent energy flux.

turbulent boundary layers↗

Fully three-dimensional simulation and modeling of a dense plasma focus

A dense plasma focus (DPF) is a pulsed-power machine that electromagnetically accelerates and cylindrically compresses a shocked plasma in a Z-pinch. The pinch results in a brief (~ 100 ns) pulse of X-rays, and, for some working gases, also a pulse of neutrons. A great deal of experimental research has been done into the physics of DPF reactions, and there exist mathematical models describing its behavior during the different time phases of the reaction. Two of the phases, known as the inverse pinch and the rundown, are approximately governed by magnetohydrodynamics, and there are a number of well-established codes for simulating these phases in two dimensions or in three dimensions under the assumption of axial symmetry. There has been little success, however, in developing fully three-dimensional simulations. In this work we present three-dimensional simulations of DPF reactions and demonstrate that three-dimensional simulations predict qualitatively and quantitatively different behavior than their two-dimensional counterparts. One of the most important quantities to predict is the time duration between the formation of the gas shock and Z-pinch, and the three-dimensional simulations more faithfully represent experimental results for this time duration and are essential for accurate prediction of future experiments.

Dense plasma focus, magnetohydrodynamics, simulati↗

A top-down assessment using OMI NO 2 suggests an underestimate in the NO x emissions inventory in Seoul, South Korea, during KORUS-AQ

Abstract. In this work, we investigate the NO x emissions inventory inSeoul, South Korea, using a regional ozone monitoring instrument (OMI) NO 2 product derived from the standard NASA product. We first develop a regional OMI NO 2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO 2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO 2 values in the regional product that are1.37 times larger in the Seoul metropolitan region and &gt;2 times larger near substantial point sources. These two modifications also yield an OMI NO 2 product that is in better agreement with the Pandora NO 2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NO x emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO 2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NO x emissions rate of 227±94 kt yr –1 , while the bottom-up inventory itself within a 40 km radius of Seoul yields a NO x emissions rate of198 kt yr –1 . Using the top-down approach on the regional OMI NO 2 product, we derive the NO x emissions rate from Seoul to be 484±201 kt yr –1 , and a 353±146 kt yr –1 NO x emissions rate using the standard NASA OMI NO 2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO 2 products respectively. To supplement this finding, we compare the NO 2 and NO y simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate.When NO x emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO 2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF),there are small differences ( ~8 %) in OMI NO 2 compared tousing the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Furthermore the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NO x emissions estimates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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