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At least 37 records · Page 2

Experimental spectrum averaged cross sections (SACS) in 252 Cf(sf) neutron field and its impact on the evaluation of neutron standards

A new evaluation of spectrum averaged cross sections (SACS) of 235 U, 238 U, and 239 Pu measured in the 252 Cf(sf) reference neutron field is presented and found to be consistent with the original Mannhart SACS evaluation in IRDF-2002. The comprehensive vetted experimental database that includes SACS ratio and absolute SACS measurements of major actinides is being used to update the SACS database employed as input of the new GMApy code to derive the Neutron Standards. An update of the current neutron standards based on Time Projection Chamber (TPC) shape data, a new comprehensive uncertainty quantification, and revised SACS experimental database is proposed which result in a 0.7% increase of the evaluated 239 Pu(n,f)/ 235 U(n,f) crosssection ratio in the 1–5 MeV energy region. The increase is due to a 0.3% reduction of the standard 235 U(n,f) cross section and a 0.4% increase of the 239 Pu(n,f) reference cross section in the 1–5 MeV energy region. Those changes are well within estimated USU fission cross-section uncertainties of 1.2%, but are relevant for the evaluated mean values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hybrid Wing Body Aircraft System Noise Assessment with Propulsion Airframe Aeroacoustic Experiments

A system noise assessment of a hybrid wing body configuration was performed using NASA s best available aircraft models, engine model, and system noise assessment method. A propulsion airframe aeroacoustic effects experimental database for key noise sources and interaction effects was used to provide data directly in the noise assessment where prediction methods are inadequate. NASA engine and aircraft system models were created to define the hybrid wing body aircraft concept as a twin engine aircraft with a 7500 nautical mile mission. The engines were modeled as existing technology high bypass ratio turbofans. The baseline hybrid wing body aircraft was assessed at 22 dB cumulative below the FAA Stage 4 certification level. To determine the potential for noise reduction with relatively near term technologies, seven other configurations were assessed beginning with moving the engines two fan nozzle diameters upstream of the trailing edge and then adding technologies for reduction of the highest noise sources. Aft radiated noise was expected to be the most challenging to reduce and, therefore, the experimental database focused on jet nozzle and pylon configurations that could reduce jet noise through a combination of source reduction and shielding effectiveness. The best configuration for reduction of jet noise used state-of-the-art technology chevrons with a pylon above the engine in the crown position. This configuration resulted in jet source noise reduction, favorable azimuthal directivity, and noise source relocation upstream where it is more effectively shielded by the limited airframe surface, and additional fan noise attenuation from acoustic liner on the crown pylon internal surfaces. Vertical and elevon surfaces were also assessed to add shielding area. The elevon deflection above the trailing edge showed some small additional noise reduction whereas vertical surfaces resulted in a slight noise increase. With the effects of the configurations from the database included, the best available noise reduction was 40 dB cumulative. Projected effects from additional technologies were assessed for an advanced noise reduction configuration including landing gear fairings and advanced pylon and chevron nozzles. Incorporating the three additional technology improvements, an aircraft noise is projected of 42.4 dB cumulative below the Stage 4 level.

Thomas, Russell H.↗

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparison of Zirconium Redistribution in BISON EBR-II Models Using FIPD and IMIS Databases with Experimental Post Irradiation Examination

Metallic fuels have seen increased interest for future sodium fast reactors due to their material properties: high thermal conductivities and advantageous neutronic properties allow for greater fission densities. One drawback to typical metallic fuels is zirconium redistribution, which impacts this advantageous material and its neutronic properties. Unfortunately, the processes behind zirconium migration behavior are understood using first principles, so before these fuels are implemented in future fast reactors, characterization and fuel qualification regimes must be completed. These activities can be supported through the use of robust modeling using the most accurate empirical models currently available to fuel researchers around the world. The tool that allows researchers to model this complex coupled thermo-mechanical behavior and nuclear properties is BISON. Additionally, BISON model parameters need to be compared against PIE measurements. The current work utilizes two fuel pins from EBR-II experiment X441 to optimize various model parameters, including porosity correction factor, thermal conductivity, phase transition temperature, and diffusion coefficient multipliers, before implementing the final model for seven fuel pins with differing characteristics. To properly evaluate the BISON simulations, the results are compared to PIE metallography data for each fuel pin, to ensure the zirconium redistribution is properly reflected in the simulation results. Six out of seven analyzed fuel pins demonstrate good agreement between the metallography images and BISON results, showing alignment of the Zr-rich, Zr-depleted, and moderately Zr-enriched zones at various axial heights along the fuel pins. Further work is needed to refine the model parameters for general pin use.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparison of zirconium redistribution in BISON EBR-II models using FIPD and IMIS databases with experimental Post Irradiation Examination

The BISON code framework is utilized to model and analyze zirconium redistribution within UPuZr metallic fuels. The simulation results are compared against past experimental metallography data to validate the BISON code models. Various BISON models are implemented and compared to properly reflect the Zr present in past data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ATR NEXSHARE Fact Sheet

This fact sheet will provide information for the database of experimental facilities supported by the IAEA as outlined below: NEXSHARE: As part of the Nuclear Harmonization and Standardization Initiative (NHSI), the IAEA proposes to establish a Network for global cooperation and resource sharing for experiments and code validation between experimental facilities, SMRs design organizations, International Organizations and Technical Support Organizations (TSOs). The proposed Network, NEXSHARE, will be done in collaboration with the OECD/NEA. EXPERIMENTAL FACILITY DATABASE: As part of this activity, the IAEA is compiling a database of experimental facilities applicable to SMRs (including water cooled, high temperature gas cooled, molten salt and fast neutron spectrum reactors). This database will also form part of NEXSHARE and will be documented in an IAEA publication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

[Tail Plane Icing]

The Aviation Safety Program initiated by NASA in 1997 has put greater emphasis in safety related research activities. Ice-contaminated-tailplane stall (ICTS) has been identified by the NASA Lewis Icing Technology Branch as an important activity for aircraft safety related research. The ICTS phenomenon is characterized as a sudden, often uncontrollable aircraft nose- down pitching moment, which occurs due to increased angle-of-attack of the horizontal tailplane resulting in tailplane stall. Typically, this phenomenon occurs when lowering the flaps during final approach while operating in or recently departing from icing conditions. Ice formation on the tailplane leading edge can reduce tailplane angle-of-attack range and cause flow separation resulting in a significant reduction or complete loss of aircraft pitch control. In 1993, the Federal Aviation Authority (FAA) and NASA embarked upon a four-year research program to address the problem of tailplane stall and to quantify the effect of tailplane ice accretion on aircraft performance and handling characteristics. The goals of this program, which was completed in March 1998, were to collect aerodynamic data for an aircraft tail with and without ice contamination and to develop analytical methods for predicting the effects of tailplane ice contamination. Extensive dry air and icing tunnel tests which resulted in a database of the aerodynamic effects associated with tailplane ice contamination. Although the FAA/NASA tailplane icing program generated some answers regarding ice-contaminated-tailplane stall (ICTS) phenomena, NASA researchers have found many open questions that warrant further investigation into ICTS. In addition, several aircraft manufacturers have expressed interest in a second research program to expand the database to other tail configurations and to develop experimental and computational methodologies for evaluating the ICTS phenomenon. In 1998, the icing branch at NASA Lewis initiated a second multi-phase research program for tailplane icing (TIP II) to develop test methodologies and tailplane performance and handling qualities evaluation tools. The main objectives of this new NASA/Industry/Academia collaborative research programs were: (1) define and evaluate a sub-scale wind tunnel test methodology for determining tailplane performance degradation due to icing. (2) develop an experimental database of tailplane aerodynamic performance with and without ice contamination for a range of tailplane configurations. Wind tunnel tests were planned with representative general aviation aircraft, i.e., the Learjet 45, and a twin engine low speed aircraft. This report summarizes the research performed during the first year of the study, and outlines the work tasks for the second year.

Source record↗

A database of aerothermal measurements in hypersonic flow for CFD validation

This paper presents an experimental database selected and compiled from aerothermal measurements obtained on basic model configurations on which fundamental flow phenomena could be most easily examined. The experimental studies were conducted in hypersonic flows in 48-inch, 96-inch, and 6-foot shock tunnels. A special computer program was constructed to provide easy access to the measurements in the database as well as the means to plot the measurements and compare them with imported data. The database contains tabulations of model configurations, freestream conditions, and measurements of heat transfer, pressure, and skin friction for each of the studies selected for inclusion. The first segment contains measurements in laminar flow emphasizing shock-wave boundary-layer interaction. In the second segment, measurements in transitional flows over flat plates and cones are given. The third segment comprises measurements in regions of shock-wave/turbulent-boundary-layer interactions. Studies of the effects of surface roughness of nosetips and conical afterbodies are presented in the fourth segment of the database. Detailed measurements in regions of shock/shock boundary layer interaction are contained in the fifth segment. Measurements in regions of wall jet and transpiration cooling are presented in the final two segments.

Holden, M. S.↗

High-Throughput Ion Irradiation and Microstructural Characterization of Multi-Principal-Element Alloys

Multi-principal-element alloys (MPEAs) have garnered interest in the nuclear community for their apparent resistance to microstructural damage under irradiation. While both experimentation and simulation have demonstrated reduced hardening and void swelling in MPEAs, the relationship between composition and irradiation response is still poorly understood since a rich experimental database for MPEAs does not yet exist. In this work, to accelerate the generation of experimental irradiation-response data for MPEAs, high-throughput synthesis, irradiation, and characterization techniques have been employed. Specifically, additive manufacturing has been used to produce arrays of various MPEAs (1-cm2 coupons), which have been subsequently irradiated using 4-MeV Ni2+ ions to a peak damage of 200 dpa at 500 °C. Hardening and void swelling have been assessed using nanoindentation and trenching via plasma focused ion beam (PFIB), respectively. Trends in the experimental data relating hardening and void swelling behavior to composition have been analyzed using different machine learning approaches.

36 MATERIALS SCIENCE↗

Experimental and Numerical Investigation of Reduced Gravity Fluid Slosh Dynamics for the Characterization of Cryogenic Launch and Space Vehicle Propellants

As space programs increasingly investigate various options for long duration space missions the accurate prediction of propellant behavior over long periods of time in microgravity environment has become increasingly imperative. This has driven the development of a detailed, physics-based understanding of slosh behavior of cryogenic propellants over a range of conditions and environments that are relevant for rocket and space storage applications. Recent advancements in computational fluid dynamics (CFD) models and hardware capabilities have enabled the modeling of complex fluid behavior in microgravity environment. Historically, launch vehicles with moderate duration upper stage coast periods have contained very limited instrumentation to quantify propellant stratification and boil-off in these environments, thus the ability to benchmark these complex computational models is of great consequence. To benchmark enhanced CFD models, recent work focuses on establishing an extensive experimental database of liquid slosh under a wide range of relevant conditions. In addition, a mass gauging system specifically designed to provide high fidelity measurements for both liquid stratification and liquid/ullage position in a micro-gravity environment has been developed. This pUblication will summarize the various experimental programs established to produce this comprehensive database and unique flight measurement techniques.

Walls, Laurie K.↗

Characterization of local parameters of inclined upward air–water bubbly two-phase flows in a round pipe

The present work seeks to develop a detailed experimental database and characterize the local effects of inclination on horizontal and upward bubbly air–water two-phase flows. Experimental conditions are selected to investigate bubbly flows at a variety of orientations while reducing the influence of flow regime transition. Detailed time-averaged data is collected using state-of-the-art four-sensor conductivity probes for measurements across the flow area for five flow conditions at five inclination orientations in a 25.4 mm inner diameter pipe. Using the newly established database, effects of inclination on bubbly flows are analyzed, as are changes in liquid and gas flow rate at different orientations. The observations include (1) bubble migration and agglomeration at the top pipe wall as orientation changes from vertical to horizontal; (2) reducing the angle from vertical reduces the local gas velocity, and correspondingly reduces the global slip from greater than unity at 90° to less than unity for 60° and lower; (3) changes in the bubble size distribution are primarily at the interface between the bubble cluster and the liquid region of the pipe, not coalescence within the bubble cluster. In conclusion, physical mechanisms for these observations are proposed, and the present trends at different orientations support previous experiments in horizontal two-phase flows.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Assessment of NASA's Aircraft Noise Prediction Capability

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

Dahl, Milo D.↗

WPEC SG50: Developing an Automatically Readable, Comprehensive and Curated Experimental Nuclear Reaction Database

The Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Co-operation (WPEC) subgroup (SG) 50 was formed in 2020 to develop an automatically readable, comprehensive and curated experimental nuclear reaction database. This database is called MEDUSAL (Machine-readable Experimental Data User Application & Library), and will draw from EXFOR. The EXFOR database preserves experimental nuclear reaction data true to its original documentation and information from the authors of the data. MEDUSAL will deviate from EXFOR by storing additional information from users of the data for their fields of work (evaluation, model development, validation, etc.). This includes expert judgment on the data sets, identification of data points as outliers, renormalization of the data to the newest monitor reactions, and estimations of missing uncertainty sources. The format for MEDUSAL is being developed to enable easy automatic parsing of large amounts of data. Here, we will summarize the use cases, high-level requirements and first steps towards developing the database MEDUSAL and the API to access it.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

What Machine Learning Can and Cannot Do for Inertial Confinement Fusion

Machine learning methodologies have played remarkable roles in solving complex systems with large data, well-defined input–output pairs, and clearly definable goals and metrics. The methodologies are effective in image analysis, classification, and systems without long chains of logic. Recently, machine-learning methodologies have been widely applied to inertial confinement fusion (ICF) capsules and the design optimization of OMEGA (Omega Laser Facility) capsule implosion and NIF (National Ignition Facility) ignition capsules, leading to significant progress. As machine learning is being increasingly applied, concerns arise regarding its capabilities and limitations in the context of ICF. ICF is a complicated physical system that relies on physics knowledge and human judgment to guide machine learning. Additionally, the experimental database for ICF ignition is not large enough to provide credible training data. Most researchers in the field of ICF use simulations, or a mix of simulations and experimental results, instead of real data to train machine learning models and related tools. They then use the trained learning model to predict future events. This methodology can be successful, subject to a careful choice of data and simulations. However, because of the extreme sensitivity of the neutron yield to the input implosion parameters, physics-guided machine learning for ICF is extremely important and necessary, especially when the database is small, the uncertain-domain knowledge is large, and the physical capabilities of the learning models are still being developed. In this work, we identify problems in ICF that are suitable for machine learning and circumstances where machine learning is less likely to be successful. This study investigates the applications of machine learning and highlights fundamental research challenges and directions associated with machine learning in ICF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The NASA Hyper-X Program

This paper provides an overview of NASA's Hyper-X Program; a focused hypersonic technology effort designed to move hypersonic, airbreathing vehicle technology from the laboratory environment to the flight environment. This paper presents an overview of the flight test program, research objectives, approach, schedule and status. Substantial experimental database and concept validation have been completed. The program is currently concentrating on the first, Mach 7, vehicle development, verification and validation in preparation for wind-tunnel testing in 1998 and flight testing in 1999. Parallel to this effort the Mach 5 and 10 vehicle designs are being finalized. Detailed analytical and experimental evaluation of the Mach 7 vehicle at the flight conditions is nearing completion, and will provide a database for validation of design methods once flight test data are available.

Freeman, Delman C., Jr.↗

Evaluation of an Impedance Model for Perforates Including the Effect of Bias Flow

A new bias flow impedance model is developed for perforated plates from basic principles using as little empiricisms as possible. A quality experimental database was used to determine the predictive validity of the model. Results show that the model performs better for higher (15%) rather than lower (5%) percent open area (POA) samples. Based on the least squares ratio of numerical vs. experimental results, model predictions were on average within 20% and 30% for the higher and lower (POA), respectively. It is hypothesized on the work of other investigators that at lower POAs the higher fluid velocities in the perforate's orifices start forming unsteady vortices, which is not accounted for in our model. The numerical model, in general also underpredicts the experiments. It is theorized that the actual acoustic C(sub D) is lower than the measured raylometer C(sub D) used in the model. Using a larger C(sub D) makes the numerical model predict lower impedances. The frequency domain model derived in this paper shows very good agreement with another model derived using a time domain approach.

Betts, J. F.↗

Integrated Computational Materials and Mechanical Modeling for Additive Manufacturing of Alloys with Graded Structure Used in Fossil Fuel Power Plants

Wire-arc additive manufacturing (WAAM) has demonstrated its unique capability of producing large-size alloy components with a significantly reduced fabrication time and enhanced geometry design freedom. In this project, the team has developed an ICME (Integrated Computational Materials Engineering) modeling framework, which supports the WAAM of the AUSC (Advanced Ultra-Supercritical) power plant components. The manufacturing design has been applied to Inconel 740H, steel P91, as well as the dissimilar alloy components between steel P91 and Inconel 740H. The ICME model framework is developed by considering two types of modeling. First, mechanistic modeling has been applied to control the printing quality and understand the sequence of the dissimilar printing of the wall structure. The following models have been included in the developed ICME framework: finite element thermal model, grain structure model, residual stress simulation, crystal plasticity model, CALPHAD-based precipitation kinetic model, phase stability prediction, thermal expansion predictive model, and heuristic creep model. Secondary, a physics-based machine learning model has also been developed based on the ICME model structure. The machine learning model development is based on the ICME model prediction with calibration of the experiments. In addition, the WAAM has been utilized as a high-throughput experimental tool rapidly generating a gradient of alloy composition to facilitate experimental database generation for process-structure-property relationships. Such a database directly supported the ICME-enhanced machine learning, which further assisted in intermediate composition block design between P91 and 740H. A high-throughput screening study of the oxidation resistance has been performed based on such high-throughput experimentation. Based on the computational design, several dissimilar alloy manufacturing with post-heat treatment have been performed with a comprehensive evaluation of mechanical performance, including hardness mapping, yield strength, creep resistance. In this project, the single component of P91 and 740H processed by WAAM after heat treatment designed by ICME has demonstrated higher performance in yield strength and creep resistance than the wrought materials. The P91 sample prepared by WAAM with ICME-designed heat treatment performs better than P92 in creep resistance. The designed graded alloy printing with intermediate block shows a promising performance that exceeds the traditional welding. Moreover, the current research indicates the high need for location-specific design analysis with uncertainty quantification, an important topic that deserves more dedicated research. The achievement of this project demonstrated the promising future of WAAM in structural alloy manufacturing for energy power plant development. Successful printing requires synergetic efforts made by manufacturing, mechanical, and materials sciences.

20 FOSSIL-FUELED POWER PLANTS↗

Flow Control Analysis on the Hump Model with RANS Tools

A concerted effort is underway at NASA Langley Research Center to create a benchmark for Computational Fluid Dynamic (CFD) codes. both unstructured and structured, against a data set for the hump model with actuation. The hump model was tested in the NASA Langley 0.3-m Transonic Cryogenic Tunnel. The CFD codes used for the analyses are the FUN2D (Full Unstructured Navier-Stokes 2-Dimensional) code, the structured TLNS3D (Thin-Layer Navier-Stokes 3-Dimensional) code, and the structured CFL3D code, all developed at NASA Langley. The current investigation uses the time-accurate Reynolds-Averaged Navier-Stokes (RANS) approach to predict aerodynamic performance of the active flow control experimental database for the hump model. Two-dimensional computational results verified that steady blowing and suction and oscillatory suction/blowing can be used to significantly reduce the separated flow region on the model. Discrepancies do exist between the CFD results and experimental data in the region downstream of the slot with the largest differences in the oscillatory cases. Overall, the structured CFD codes exhibited similar behavior with each other for a wide range of control conditions, with the unstructured FUN2D code showing moderately different results in the separated flow region for the suction and oscillatory cases.

Viken, Sally A.↗