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At least 595 records · Page 33

Survey of engineering computational methods and experimental programs for estimating supersonic missile aerodynamic characteristics

This paper presents a survey of engineering computational methods and experimental programs used for estimating the aerodynamic characteristics of missile configurations. Emphasis is placed on those methods which are suitable for preliminary design of conventional and advanced concepts. An analysis of the technical approaches of the various methods is made in order to assess their suitability to estimate longitudinal and/or lateral-directional characteristics for different classes of missile configurations. Some comparisons between the predicted characteristics and experimental data are presented. These comparisons are made for a large variation in flow conditions and model attitude parameters. The paper also presents known experimental research programs developed for the specific purpose of validating analytical methods and extending the capability of data-base programs.

Sawyer, W. C.↗

Development of Critical Experiments to Provide Validation Data for Multiphysics Coupling Methods (Final Report)

Computational simulation has become one of the most important tools in the modern toolbox for nuclear reactor design. Reactor simulations, like the reactors themselves, involve multiple physical processes including neutronics, fluid flow and heat transfer (thermal-hydraulics), thermo-mechanics, fuel behavior, chemistry, and balance of plant. Each process can affect the behavior of the others, and advanced computational tools have been developed that couple separate physics models together to simulate the feedback effects. The objective of this work is to generate experimental data to support the validation of multi-physics reactor codes. It specifically targets the SHARP toolset from the NEAMS Reactor Product Line, but it is intended to be useful in any set of coded that couples thermal-hydraulics with neutronics simulations. The project takes advantage of the inherent flexibility of the RPI Reactor Critical Facility (RCF), a low power open-pool research reactor. The standard configuration of the RCF is used to explore the effects of moderator temperature on neutronic behavior and reactivity. Because the low power of the reactor generates no appreciable temperature change in the moderator, the moderator temperature is artificially changed with two 18 kW electric immersion heaters. The temperature feedback effects can be observed by recording the change in the reactor power as the reactor goes from a supercritical state, to critical, to a subcritical state. To expand the temperature range and temperature rate of change that can be investigated, an experimental apparatus consisting of a heated water loop was designed and installed in the RCF. In this setup, water from a heated reservoir tank is pumped through a pipe placed through the center of the reactor core. The water in the reservoir can be heated to around 70 °C and pumped through the system. The pump has a variable flow rate and electronic control, so a number of scenarios can be developed. A slug of water can be pushed through the system to generate a reasonably fast change in reactivity. The pump speed can be increased or decreased over the course of a measurement, or even oscillated at different periods, to observe the response of the reactor. To complement the experimental data generated by the RCF, a set of computational models have been developed. They are intended to illustrate the usefulness of the experimental data generated in validating coupled multi-physics simulations. A model previously constructed in MCNP has been used in conjunction with safety analysis at the RCF for many years and was modified to support the design of the heated water loop experiment. This model was translated into Serpent 2, a similar Monte Carlo code, which provided the added advantage of being able to produce collapsed cross-section data files for use in the deterministic neutron transport codes that are part of the SHARP toolset. A complete reconstruction of the RCF model, both with and without the heated fluid loop experiment, were necessary for use with the SHARP codes, PROTEUS (neutronics) and Nek5000 (thermal hydraulics), as these require an unstructured mesh format to operate. The computational requirements for fully coupled three dimensional simulations are significant, and challenges to full implementation and comparison with RCF experiments remain. A wide variety of experiments have been conducted for eventual benchmarking and validation of multi-physics reactor codes. A complete database of detailed time- and temperature-dependent measurements have been generated and stored. Several examples of the experimental results are presented here, with refinement and analysis of experiments ongoing. While these experiments still only address a finite range of operating conditions, in particular being limited to water in the sub-boiling regime, they represent a unique (to date) look at the feedback between temperature and neutronic behavior suited for validation of the coupling routines in multi-physics codes. It is hoped that these will be the foundation of future benchmarks that will provide confidence in the tools that will be used to develop the next generation of nuclear reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Estimating Vibrational Powers Of Parts In Fluid Machinery

In new method of estimating vibrational power associated with component of fluid-machinery system, physics of flow through (or in vicinity of) component regarded as governing vibrations. Devised to generate scaling estimates for design of new parts of rocket engines (e.g., pumps, combustors, nozzles) but applicable to terrestrial pumps, turbines, and other machinery in which turbulent flows and vibrations caused by such flows are significant. Validity of method depends on assumption that fluid flows quasi-steadily and that flow gives rise to uncorrelated acoustic powers in different parts of pump.

Harvey, S. A.↗

A hybrid calibration approach to Hertz-type contact parameters for discrete element models

This study aims at providing a hybrid calibration framework to estimate Hertz-type contact parameters (particle-scale shear modulus and Poisson ratio) for both two-dimensional and three-dimensional discrete element modelling (DEM). On the basis of statistically isotropic granular packings, a set of analytical formulae between macroscopic material parameters (Young modulus and Poisson ratio) and particle-scale Hertz-type contact parameters for granular systems are derived under small-strain isotropic stress conditions. However, the derived analytical solutions are only estimated values for general models. By viewing each DEM modelling as an implicit mathematical function taking the particle-level parameters as independent variables and employing the derived analytical solutions as the initial input parameters, an automatic iterative scheme is proposed to obtain the calibrated parameters with higher accuracies. Considering highly nonlinear features and discontinuities of the macro-micro relationship in Hertz-based discrete element models, the adaptive moment estimation algorithm is adopted in this study because of its capacity of dealing with noise gradients of cost functions. Here, the proposed method is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. Noticeable improvements in terms of calibration efficiency and accuracy have been made.

Constitutive law↗

Radiation-Induced Lens Opacities among Interventional Cardiologists: Retrospective Assessment of Cumulative Eye Lens Doses

This study describes the retrospective lens dose calculation methods developed and applied within the European epidemiological study on radiation-induced lens opacities among interventional cardiologists. While one approach focuses on self-reported data regarding working practice in combination with available procedure-specific eye lens dose values, the second approach focuses on the conversion of the individual whole-body dose to eye lens dose. In contrast with usual dose reconstruction methods within an epidemiological study, a protocol is applied resulting in an individual distribution of possible cumulative lens doses for each recruited cardiologist, rather than a single dose estimate. In this way, the uncertainty in the dose estimate (from measurement uncertainty and variability among cardiologists) is represented for each individual. Eye lens dose and whole-body dose measurements have been performed in clinical practice to validate both methods, and it was concluded that both produce acceptable results in the framework of a dose-risk evaluation study. Optimal results were obtained for the dose to the left eye using procedure-specific lens dose data in combination with information collected on working practice. This method has been applied to 421 interventional cardiologists resulting in a median cumulative eye lens dose of 15.1 cSv for the left eye and 11.4 cSv for the right eye. From the individual cumulative eye lens dose distributions obtained for each cardiologist, maxima up to 9-10 Sv were observed, although with low probability. Since whole-body dose values above the lead apron are available for only a small fraction of the cohort and in many cases not for the entire working career, the second method has only been used to benchmark the results from the first approach. This study succeeded in improving the retrospective calculation of cumulative eye lens doses in the framework of radiation-induced risk assessment of lens opacities, but it remains dependent on self-reported information, which is not always reliable for early years. However, the calculation tools developed can also be used to make an assessment of the eye lens dose in current practice.

61 RADIATION PROTECTION AND DOSIMETRY↗

Big-Data Multi-Energy Iterative Volumetric Reconstruction Methods for As-Built Validation & Verification Applications

This document archives the results developed by the Lab Directed Research and Development (LDRD) project sponsored by Sandia National Laboratories (SNL). In this work, it is shown that SNL has developed the first known high-energy hyperspectral computed tomography system for industrial and security applications. The main results gained from this work include dramatic beam-hardening artifact reduction by using the hyperspectral reconstruction as a bandpass filter without the need for any other computation or pre-processing; additionally, this work demonstrated the ability to use supervised and unsupervised learning methods on the hyperspectral reconstruction data for the application of materials characterization and identification which is not possible using traditional computed tomography systems or approaches.

47 OTHER INSTRUMENTATION↗

Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data

Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.

CT↗

Small Launch Vehicle Trade Space Definition: Development of a Zero Level Mass Estimation Tool with Trajectory Validation

Recent high level interest in the capability of small launch vehicles has placed significant demand on determining the trade space these vehicles occupy. This has led to the development of a zero level analysis tool that can quickly determine the minimum expected vehicle gross liftoff weight (GLOW) in terms of vehicle stage specific impulse (Isp) and propellant mass fraction (pmf) for any given payload value. Utilizing an extensive background in Earth to orbit trajectory experience a total necessary delta v the vehicle must achieve can be estimated including relevant loss terms. This foresight into expected losses allows for more specific assumptions relating to the initial estimates of thrust to weight values for each stage. This tool was further validated against a trajectory model, in this case the Program to Optimize Simulated Trajectories (POST), to determine if the initial sizing delta v was adequate to meet payload expectations. Presented here is a description of how the tool is setup and the approach the analyst must take when using the tool. Also, expected outputs which are dependent on the type of small launch vehicle being sized will be displayed. The method of validation will be discussed as well as where the sizing tool fits into the vehicle design process.

Waters, Eric D.↗

Tackling the curse of dimensionality in fractional and tempered fractional PDEs with physics-informed neural networks

Fractional and tempered fractional partial differential equations (PDEs) are effective models of long-range interactions, anomalous diffusion, and non-local effects. Traditional numerical methods for these problems are mesh-based, thus struggling with the curse of dimensionality (CoD). Physics-informed neural networks (PINNs) offer a promising solution due to their universal approximation, generalization ability, and mesh-free training. In principle, Monte Carlo fractional PINN (MC-fPINN) estimates fractional derivatives using Monte Carlo methods and thus could lift CoD. However, this may cause significant variance and errors, hence affecting convergence; in addition, MC-fPINN is sensitive to hyperparameters. In general, numerical methods and specifically PINNs for tempered fractional PDEs are under-developed. Herein, we extend MC-fPINN to tempered fractional PDEs to address these issues, resulting in the Monte Carlo tempered fractional PINN (MC-tfPINN). To reduce possible high variance and errors from Monte Carlo sampling, we replace the one-dimensional (1D) Monte Carlo with 1D Gaussian quadrature, applicable to both MC-fPINN and MC-tfPINN. We validate our methods on various forward and inverse problems of fractional and tempered fractional PDEs, scaling up to 100,000 dimensions. Our improved MC-fPINN/MC-tfPINN using quadrature consistently outperforms the original versions in accuracy and convergence speed in very high dimensions.

42 ENGINEERING↗

Azimuthally-dependent Finite Element Solution to the Cylindrical Resonator

The cylindrical cavity resonator loaded with an anisotropic dielectric is analyzed as a two-dimensional problem using a finite element approach that assumes sinusoidal dependence in azimuth. This methodology allows the first finite element treatment of the technically important case of a resonator containing a sapphire element with a cylindrically aligned c axis. Second order trial functions together with quadrilateral elements are adopted in the calculations. The method was validated through comparisons with the analytical solutions for the hollow metal cavity and a coaxial cavity, as well as through measurements on a shielded sapphire resonator.

cylindrical resonator two-dimensional finite eleme↗

Lost and Found Opportunities Around the Chlorine Worth Study

Los Alamos National Laboratory performed a series of critical experiments in 2021 to examine the worth of chlorine in plutonium-fueled systems. This series of experiments has been dubbed the “Chlorine Worth Study,” and the evaluation of the experiments was presented to the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Technical Review Group in April, 2023. The primary purpose of these experiments was to enable validation of aqueous solutions crediting neutron absorption in 35 Cl. An external, independent view of the events leading up to the design and execution of these experiments indicates a missed opportunity to leverage sensitivity/uncertainty (S/U) analysis to assert validation without the experiments by taking an additional margin for the lack of direct validation of chlorine. On the other hand, the execution of these experiments also presents a rare opportunity to examine the efficacy of the S/U approach and extract useful information about the evaluated chlorine covariance data. TSUNAMI-1D models of representative application solutions were created and used to generate sensitivity data. Varying plutonium and chlorine concentrations were considered to examine the impact of these differences on the chlorine sensitivities and uncertainties. The data-induced uncertainty in k eff resulting from chlorine was calculated directly from uncertainty information calculated in the TSUNAMI-1D sequence. In all cases, this uncertainty was less than 0.1 %Δk. This result could potentially be used to justify a reactivity margin to account for the validation gap related to chlorine in the validation set. On the other hand, given that the experiments were performed, the community should endeavor to extract as much value from them and their results as possible. The results can be used to examine the actual bias associated with chlorine in these systems once the evaluations have been released. These data can be compared with the data-induced uncertainty margin discussed above to test the sufficiency of the validation gap penalty. This result will provide an indication of the performance of the chlorine covariance data specifically and the S/U validation approach generally. More advanced S/U techniques may also be employed to determine reactivity sensitivities associated with the chlorine in the experiments, potentially generating a more robust test of the chlorine covariance data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evolving Applications of Aerosol Sealant

Solving the issues facing the residential building industry today requires developing not only new technologies but also new, innovative applications of existing high-performance technologies. The U.S. Department of Energy's (DOE's) Building America Program is using this approach to develop a low-cost, easy solution for whole-home envelope air sealing. Aerosol sealant is a proven method for sealing ducts quickly and efficiently, especially in hard-to-reach places. This technology, originally developed at Lawrence Berkeley National Laboratory in 1994 with support from DOE, seals 70%-90% of duct leaks (LBNL n.d.), saving $600-$850 per year in energy costs for an average household (DOE 2011). A new, innovative application takes this technology out of the duct system and into the conditioned space. Recent Building America projects have validated a method for whole-house air sealing using the aerosol sealant technology. With tighter envelope requirements in new codes and above-code programs, adequately air sealing by hand is more labor-intensive and costly than ever. The aerosol sealing method is designed to eliminate the guesswork and automate this process. The continuous measurement during installation allows builders to dial in the exact air tightness they need to meet their performance goals. Initial field testing shows that this method regularly achieves air leakage levels less than 1 ACH50 as measured by a blower door test. In a current Building America project, the Center for Energy and Environment is performing iterative field tests in 20 homes to identify the optimal integration and sequencing of this method in production home building processes to achieve a lower installation cost than traditional air sealing. This method has the potential to improve quality assurance of envelope sealing and significantly reduce labor costs compared with traditional air sealing approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dual-Channel Enzymatic Inhibition Measurement (DEIM) Coupling Isotope Substrate via Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry

A novel dual-channel enzymatic inhibition measurement (DEIM) method was developed to improve the repeatability with light/heavy isotope substrates, producing reliable relative standard deviations (< 3%) by employing acetylcholinesterase (AChE) as the model enzyme. The matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) was adapted for enzyme-inhibited method due to its good salt-tolerance and high throughput; meanwhile, dual-channel enzymatic reactions were performed to improve the repeatability of each well. The acetylcholinesterase inhibition measurement was conducted by mixing the quenched enzyme reaction solution of blank group (with heavy isotope as substrate) and experimental group (with light isotope as substrate), of which the inhibition rate might be affected by isotope effects. Hence, inverse study and Km measurement were implemented to validate the method. The inverse study shows similar inhibition rate (68.9 and 70.3%) and the Km of isotope substrates are analogous (0.139 and 0.135 mM), which demonstrated that the novel method is feasible to AChE inhibition measurement. Finally, the method was applied to herb extracts, half of which exhibit inhibition to AChE. The precise dual-channel enzymatic inhibition measurement (DEIM) method could be regarded as a promising approach to potential enzyme inhibitor screening. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Solar extreme ultraviolet sensor and advanced langmuir probe

For more than two decades, the staff of the Space Physics Research Laboratory (SPRL) has collaborated with the Goddard Space Flight Center (GSFC) in the design and implementation of Langmuir probes (LP). This program of probe development under the direction of Larry Brace of GSFC has evolved methodically with innovations to: improve measurement precision, increase the speed of measurement, and reduce the weight, size, power consumption and data rate of the instrument. Under contract NAG5-419 these improvements were implemented and are what characterize the Advanced Langmuir Probe (ALP). Using data from the Langmuir Probe on the Pioneer Venus Orbiter, Brace and Walter Hoegy of GSFC demonstrated a novel method of monitoring the solar extreme ultraviolet (EUV) flux. This led to the idea of developing a sensor similar to a Langmuir probe specifically designed to measure solar EUV (SEUV) that uses a similar electronics package. Under this contract, a combined instrument package of the ALP and SEUV sensor was to be designed, constructed, and laboratory tested. Finally the instrument was to be flight tested as part of sounding rocket experiment to acquire the necessary data to validate this method for possible use in future earth and planetary aeronomy missions. The primary purpose of this contract was to develop the electronics hardware and software for this instrument, since the actual sensors were suppied by GSFC. Due to budget constraints, only a flight model was constructed. These electronics were tested and calibrated in the laboratory, and then the instrument was integrated into the rocket payload at Wallops Flight Facility where it underwent environmental testing. After instrument recalibration at SPRL, the payload was reintegrated and launched from the Poker Flat Research Range near Fairbanks Alaska. The payload was successfully recovered and after refurbishment underwent further testing and developing to improve its performance for future use.

Voronka, N. R.↗

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗

Turbomachinery noise

Summarized here are key advances in experimental techniques and theoretical applications which point the way to a broad understanding and control of turbomachinery noise. On the experimental side, the development of effective inflow control techniques makes it possible to conduct, in ground based facilities, definitive experiments in internally controlled blade row interactions. Results can now be valid indicators of flight behavior and can provide a firm base for comparison with analytical results. Inflow control coupled with detailed diagnostic tools such as blade pressure measurements can be used to uncover the more subtle mechanisms such as rotor strut interaction, which can set tone levels for some engine configurations. Initial mappings of rotor wake-vortex flow fields have provided a data base for a first generation semiempirical flow disturbance model. Laser velocimetry offers a nonintrusive method for validating and improving the model. Digital data systems and signal processing algorithms are bringing mode measurement closer to a working tool that can be frequently applied to a real machine such as a turbofan engine. On the analytical side, models of most of the links in the chain from turbomachine blade source to far field observation point have been formulated. Three dimensional lifting surface theory for blade rows, including source noncompactness and cascade effects, blade row transmission models incorporating mode and frequency scattering, and modal radiation calculations, including hybrid numerical-analytical approaches, are tools which await further application.

Groeneweg, John F.↗