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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The effect of chemical functional groups on the octane sensitivity of fuel blends for spark-ignited and multimode engines

We report the octane sensitivity of fuel blends containing blendstocks of diverse chemical functionalities blended in concentrations up to 20% by volume into BOBs (Blendstocks for Oxygenate Blending). This study focuses on the blendstocks containing functional groups which lack reliable octane number data. The effects on octane sensitivity of blends of cyclopropanes, alkyl carbonates, oxiranes, alcohols, ketones, esters, nitrogen-containing compounds, cyclic and olefinic hydrocarbons, multifunctional materials containing combinations of these functionalities, and the co-blends of the blendstocks with ethanol in a BOB have been evaluated. Octane sensitivity of the blends containing functional groups that haven’t been evaluated before are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Joint inversion of gravity and cosmic ray muon flux at a well-characterised site for shallow subsurface density prediction

Estimating subsurface density is important for imaging various geologic structures such as volcanic edifices, reservoirs, and aquifers. Muon tomography has recently been used to complement traditional gravity measurements as a powerful method for probing shallow subsurface density structure beneath volcanoes. Gravity and muon data have markedly different spatial sensitivities and, as a result, the combination is useful for imaging structures on spatial scales that are larger than the area encompassed by crossing muon trajectories. Here we explore and test a joint inversion of gravity and muon data in a study area where there is an independently-characterised target anomaly: a regionally extensive, high-density layer beneath Los Alamos, New Mexico, USA. We resolve the nearly flat-lying structure using a unique experimental set-up wherein surface and subsurface gravity and muon measurements are obtained above and below the target volume. Our results show that with minimal geologic (prior) constraints, the joint inversion correctly recovers salient features of the expected density structure. The results of our study illustrate the potential of combining surface and subsurface (e.g., borehole) gravity and muon measurements to invert for shallow geologic structures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Ring laser gyroscopes in the underground Gran Sasso Laboratories

Gyroscopes IN GEneral Relativity (GINGER) is a proposed experiment with the aim of measuring the gravito-electric (known also as De Sitter effect) and gravito-magnetic effects (or Lense – Thirrings effect) in a ground laboratory, foreseen by general relativity, through an array of large dimension ring laser gyroscopes. The site is located inside the Gran Sasso laboratories (LNGS) of INFN, under more than one thousand meter underground, well protected from surface perturbations. GINGERINO is a square ring-laser prototype with 3.6 m side, which has been built to investigate the level of noise of this site. GINGERINO has already completed its task, showing the advantage of the underground location. It cannot reach the sensitivity suitable for the fundamental physics measurements, but it can provide important data for geophysics and seismology. Its high sensitivity in the frequency band of fraction of Hz and its location in a seismically active area make it suitable for seismology studies. It recorded a sequence of central Italy earthquakes in the autumn of 2016 and many other events both from near field and from far field. The analysis of 90 days of continuous operation shows that its duty cycle is higher than 95 %, with a quantum shot noise limit of the order of 10{sup −10} rad s{sup −1} Hz{sup −1/2}. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Ultra-High-Sensitivity Fiber-Optic Links STL-32-14 / STL-18-15, Year 2 of 2

Presentation describes project to develop analog fiber-optic data links based on high-sensitivity electro-optic modulators, in order to improve recording of small voltage signals in electrically noisy environments, improve the fieldability of novel modulator structures, and improve the demodulation and recording of small signals, which will enable the fielding of improved fiber links across a broad range of experimental facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

New tree-ring data from Canadian boreal and hemi-boreal forests provide insight for improving the climate sensitivity of terrestrial biosphere models

Understanding boreal/hemi-boreal forest growth sensitivity to seasonal variations in temperature and water availability provides important basis for projecting the potential impacts of climate change on the productivity of these ecosystems. Our best available information currently comes from a limited number of field experiments and terrestrial biosphere model (TBM) simulations of varying predictive accuracy. Here, we assessed the sensitivity of annual boreal/hemi-boreal forest growth in Canada to yearly fluctuations in seasonal climate variables using a large tree-ring dataset and compared this to the climate sensitivity of annual net primary productivity (NPP) estimates obtained from fourteen TBMs. We found that boreal/hemi-boreal forest growth sensitivity to fluctuations in seasonal temperature and precipitation variables changed along a southwestern to northeastern gradient, with growth limited almost entirely by temperature in the northeast and west and by water availability in the southwest. We also found a lag in growth climate sensitivity, with growth largely determined by the climate during the summer prior to ring formation. Analyses of NPP sensitivity to the same climate variables produced a similar southwest to northeast gradient in growth climate sensitivity for NPP estimates from all but three TBMs. However, analyses of growth from tree-ring data and analyses of NPP from TBMs produced contrasting evidence concerning the key climate variables limiting growth. While analyses of NPP primarily indicated a positive relationship between growth and seasonal temperature, tree-ring analyses indicated negative growth relationships to temperature. Also, the positive effect of precipitation on NPP derived from most TBMs was weaker than the positive effect of precipitation on tree-ring based growth: temperature had a more important limiting effect on NPP than tree-ring data indicated. These mismatches regarding the key climate variables limiting growth suggested that characterization of tree growth in TBMs might need revision, particularly regarding the effects of stomatal conductance and carbohydrate reserve dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A covariance methodology for theoretically generated thermal neutron inelastic scattering data - 14502

The The S(α,β) double-differential thermal neutron scattering law tabulated in ENDF File 7 is, by convention, produced theoretically through fundamental scattering physics models for material-specific interatomic structures. Differential and integral inelastic scattering cross sections are calculated by numerically integrating over S(α,β). This information is supplied to nuclear system simulation codes. For systems with a significant thermal neutron flux, calculated system response parameters can be sensitive to this thermal cross section data. Formats and procedures are currently established for representing uncertainty information, or covariances, for various types of ENDF reaction data. However, no published ENDF evaluations contain covariance data for S(α,β) or associated differential and integral inelastic scattering cross sections. Furthermore, no accepted methodology exists for quantifying or representing covariances for this thermal scattering data. For most solids, the influence of a material's interatomic structure and dynamics on inelastic scattering cross sections can be adequately described through the phonon density of states (DOS). The phonon DOS is a probability density function of the population of available vibrational modes in energy, and it is typically the fundamental input for calculating S(α,β). Probable variation in the spectral shape of the phonon DOS may be established which characterizes uncertainties in the physics models and methodology employed in its production. Through Monte Carlo sampling of perturbations from the reference phonon spectrum, an S(α,β) covariance matrix may be generated. With appropriate sensitivity information, this can be propagated to generate covariance data for differential and integral inelastic scattering cross sections. In this work, hexagonal graphite is used as an example material for the purpose of demonstrating procedures for analyzing, calculating and representing uncertainty information for thermal neutron inelastic scattering data. (authors)

42 ENGINEERING↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Minimum critical masses and their uncertainties for several fissile nuclides and reflectors - 14296

A systematic effort was undertaken to reevaluate the minimum critical mass for several fissile nuclides and reflectors. This was done using MCNP6 in combination with several modern nuclear data libraries, viz. ENDF/B-VII.1, JENDL-4.0 and JEFF-3.1.1. This combination was benchmarked extensively against criticality safety benchmarks. The procedure to extract the minimum critical mass from the MCNP6 calculations was carefully implemented, so that it would have a negligible impact on the accuracy of the end results. All parts of the calculation, i.e. nuclear data processing, MCNP6 models, and post-processing, were applied consistently for all cases, involving varying fissile nuclides and reflectors. Results for the minimum critical mass were generated for {sup 233,235}U, {sup 236,239,241}Pu, {sup 242m}Am, {sup 243,245,247}Cm, and {sup 249,251}Cf, for the case of water moderation and water reflection. For {sup 235}U, the minimum critical mass was also calculated for cases with other reflectors, such as beryllium, heavy water, graphite, lead, and concrete. The results for the water reflection cases are in good agreement with most of the literature values, but for the cases with reflectors such as graphite, lead, or concrete, there are sizable differences. The accuracy of the results was assessed in two ways. First, a comparison was made with criticality safety benchmark results, by selecting benchmarks that resemble the minimum mass systems the most. It was clear that for {sup 233,235}U and {sup 239}Pu with water reflection, the differences in minimum critical masses between the libraries are consistent with the differences obtained for benchmark cases. The difference between the benchmark calculations and the benchmark values is then an indication of the accuracy with which one can simulate comparable systems. Secondly, sensitivity runs were performed with the new MCNP6 sensitivity option, based on ENDF/B-VII.1 nuclear data. For each fissile nuclide, the sensitivity of k{sub eff} to cross sections such as capture, fission, elastic, inelastic was calculated for the minimum critical mass case. The same was done for the {sup 1}H and {sup 16}O cross sections in the moderator and reflector. The uncertainty in k{sub eff} was calculated by combining the sensitivity profiles with the appropriate ENDF/B-VII.1 covariance matrix, using the SUSD code. As a final step, the uncertainty in k{sub eff} can be translated to an uncertainty in the minimum critical mass. (author)

42 ENGINEERING↗
DOE OSTI2013

Validation of FSP Reactor Design with Sensitivity Studies of Beryllium-Reflected Critical Assemblies

The baseline design for space nuclear power is a fission surface power (FSP) system: sodium-potassium (NaK) cooled, fast spectrum reactor with highly-enriched-uranium (HEU)-O 2 fuel, stainless steel (SS) cladding, and beryllium reflectors with B4C control drums. Previous studies were performed to evaluate modeling capabilities and quantify uncertainties and biases associated with analysis methods and nuclear data. Comparison of Zero Power Plutonium Reactor (ZPPR)-20 benchmark experiments with the FSP design indicated that further reduction of the total design model uncertainty requires the reduction in uncertainties pertaining to beryllium and uranium cross-section data. Further comparison with three beryllium-reflected HEU-metal benchmark experiments performed at the Oak Ridge Critical Experiments Facility (ORCEF) concluded the requirement that experimental validation data have similar cross section sensitivities to those found in the FSP design. A series of critical experiments was performed at ORCEF in the 1960s to support the Medium Power Reactor Experiment (MPRE) space reactor design. The small, compact critical assembly (SCCA) experiments were graphite- or beryllium-reflected assemblies of SS-clad, HEU-O 2 fuel on a vertical lift machine. All five configurations were evaluated as benchmarks. Two of the five configurations were beryllium reflected, and further evaluated using the sensitivity and uncertainty analysis capabilities of SCALE 6.1. Validation of the example FSP design model was successful in reducing the primary uncertainty constituent, the Be(n,n) reaction, from 0.28 %$\delta$k/k to 0.0004 %$\delta$k/k. Further assessment of additional reactor physics measurements performed on the SCCA experiments may serve to further validate FSP design and operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Coordinated activities on evaluation of collisional data for fusion applications

It is the role of the Atomic and Molecular Data Unit of the International Atomic Energy Agency to review progress in the production, compilation and evaluation of atomic, molecular and plasma-surface interaction (AM/PSI) data for the fusion program and to support the development of internationally recommended libraries of AM/PSI data for fusion. In response to increasing requests from the fusion community the Unit has increased its effort to promote the assessment of data quality by organizing a series of meetings on the relevant issues: 1) Error propagation and sensitivity analysis, 2) Current status of evaluated databases, 3) Uncertainty estimates of theoretical data, 4) Experimental data evaluation, 5) Data evaluation methods and semi-empirical fits and 6) Establishment of an evaluators' network. The discussions and conclusions are summarized here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,↗
DOE OSTI2024

Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research

Abstract Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency’s local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Reactor simulations with nuclear data uncertainties

This work demonstrates the influence of uncertainties in microscopic nuclear data on the results of reactor simulations, both for stationary and transient states. It gives an overview on the methods in use for uncertainty and sensitivity analyses with respect to nuclear data, and discusses the pros and cons. For full-scale reactor simulations, in particular with coupled neutron transport and thermo-hydraulics, random sampling provides a powerful means to propagate nuclear data uncertainties through the complete calculation sequence. Results of uncertainty analyses performed with the GRS XSUSA – “cross section (XS) Uncertainty and Sensitivity Analysis” methodology are shown for radial power distributions from steady-state PWR calculations and for the time evolution of the reactor power in the course of a control rod withdrawal from a PWR mini-core. In all cases, the output uncertainties are considerable. For the radial power distributions, relative 1σ uncertainties of up to 10% are observed, and for the power peak during the transient, the relative 1σ uncertainty reaches 20%. These large uncertainties strongly suggest to routinely accompany best-estimate simulations by uncertainty analyses with respect to nuclear data, in particular for systems beyond LWR for which much less operation experience is available.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Abstract]

The SCALE code package offers several nuclear data libraries to support Monte Carlo (MC) transport, as well as MC-based derivation of $\kappa$ eff sensitivity and uncertainty (S/U) data. The CSAS sequence using the KENO MC code can utilize continuous-energy (CE) cross sections, or pre-generated multigroup (MG) cross section libraries. The use of MG libraries introduces bias into calculations in exchange for faster transport solutions. The TSUNAMI-3D sequence also utilizes KENO MC calculations. TSUNAMI-3D has two CE calculational methods: the Iterated Fission Probability (IFP) method, and the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method. Previous work has shown poor agreement between CLUTCH and confirmatory direct perturbation calculations in specific applications, e.g., fissionable and polyethylene reflectors

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization

How much elevated atmospheric CO2 concentration (eCO2) contributes to the terrestrial carbon sink (NEP) is a debated issue (Friedlingstein et al., 1995; Field & Raupach, 2004; Schimel et al., 2015; Keenan et al., 2016; Huntzinger et al., 2017). The results from Free-Air CO2-Enrichment (FACE) experiments at the site scale show that eCO2 generally increase plant growth and net ecosystem CO2 uptake for a few years after exposure to eCO2, but the effects were highly variable across sites (Jastrow et al., 2005; De Graaff et al., 2006), which poses a challenge for scaling up these local observations. Here, we extract the simulated short-term responses of NEP to eCO2 from global carbon models using a substitute pulse-response approach, and compare them with site-scale responses from FACE experiments in temperate ecosystems. In 12 gridded terrestrial ecosystem models examined, the large-scale NEP sensitivity to eCO2 across the Northern Hemisphere (NH) temperate region is linearly related to the site-scale sensitivity across different ecosystems. We use this emergent relationship, together with the observed response to eCO2 in the FACE site-scale data to estimate a data constrained effect of eCO2 on the NH temperate NEP of 0.73 ± 0.22 Pg C yr-1 per hundred parts per million (ppm) of CO2 increase during the past five decades. This is 26% higher than the mean of the model ensemble. Among the models, those with carbon-nitrogen interactions underestimate the sensitivity of NEP to eCO2, suggesting overly strong nitrogen-limitations on carbon uptake. We further identify that the NEP sensitivity to eCO2 at NH temperate scale is linearly correlated with that at global scale across the models. Extrapolating the constrained NH eCO2 effect to the global terrestrial carbon sink provides an estimate of 4.1 ± 1.5 Pg C yr-1 [100 ppm]-1. Large uncertainties remain regarding the global response broadly inferred from temperate FACE data, due to the lack of observations in boreal and tropical regions, emphasizing the importance of deploying new FACE experiments in those regions.

Liu, Yongwen↗
DOE OSTI2016

The advanced LIGO input optics

The advanced LIGO gravitational wave detectors are nearing their design sensitivity and should begin taking meaningful astrophysical data in the fall of 2015. These resonant optical interferometers will have unprecedented sensitivity to the strains caused by passing gravitational waves. The input optics play a significant part in allowing these devices to reach such sensitivities. Residing between the pre-stabilized laser and the main interferometer, the input optics subsystem is tasked with preparing the laser beam for interferometry at the sub-attometer level while operating at continuous wave input power levels ranging from 100 mW to 150 W. These extreme operating conditions required every major component to be custom designed. These designs draw heavily on the experience and understanding gained during the operation of Initial LIGO and Enhanced LIGO. In this article, we report on how the components of the input optics were designed to meet their stringent requirements and present measurements showing how well they have lived up to their design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

A historical analysis of the co-evolution of gasoline octane number and spark-ignition engines

In our work, the authors reviewed engine, vehicle, and fuel data since 1925 to examine the historical and recent coupling of compression ratio and fuel antiknock properties (i.e., octane number) in the U.S. light-duty vehicle market. The analysis identified historical timeframes, trends, and illustrated how three factors: consumer preferences, technical capabilities, and regulatory legislation, affect personal mobility. Data showed that throughout history these three factors have a complex and time sensitive interplay. Long term trends in the data were identified where interaction and evolution between all three factors was observed. Transportation efficiency per unit power (gal/ton-mi/hp) was found to be a good metric to integrate technical, societal, and regulatory effects into the evolutional pathway of personal mobility. From this framework, discussions of future evolutionary changes to personal mobility are also presented.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Traffic Shaping to Traffic Engineering in Time-Sensitive OT Network

Modern industrial automation systems increasingly depend on network infrastructures for time-critical communication, driving the need for solutions that guarantee timely and reliable data delivery. IEEE 802.1 Time-Sensitive Networking (TSN) holds significant promise for converging Information Technology (IT) and Operational Technology (OT) networks, enabling interoperability and supporting the coexistence of mixed-critical traffic crucial for Industry 4.0 and IIoT. To achieve deterministic communication, TSN employs various traffic shapers such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), and Credit-Based Shaper (CBS). However, the effective deployment of TSN in industrial automation faces several challenges. These include the non-trivial mapping of diverse industrial traffic types to specific shapers, the complexity of optimizing shaper configurations. We present a model for effective traffic engineering within TSN enabled OT Network. Our experiments also demonstrate how shaping of certain traffic types get affected in absence of precise time synchronization and propose possible solutions based on experiment results. Based on our experimental results we provide recommendations on how traffic type assignments should be done and which traffic shaping mechanisms should be used for a particular traffic type.

Sarker, Taposh Kumer [University of Texas at El Pa↗