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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Deprojection of X-ray data in galaxy clusters: confronting simulations with observations

ABSTRACT Numerical simulations with varying realism indicate an emergent principle−multiphase condensation and large cavity power occur when the ratio of the cooling time to the free-fall time (tcool/tff) falls below a threshold value close to 10. Observations indeed show cool-core signatures when this ratio falls below 20–30, but the prevalence of cores with tcool/tff ratio below 10 is rare as compared to simulations. In X-ray observations, we obtain projected spectra from which we have to infer radial gas density and temperature profiles. Using idealized models of X-ray cavities and multiphase gas in the core and 3D hydro jet-ICM simulations, we quantify the biases introduced by deprojection based on the assumption of spherical symmetry in determining tcool/tff. We show that while the used methods are able to recover the tcool/tff ratio for relaxed clusters, they have an uncertainty of a factor of 2−3 in systems containing large cavities (≳ 20 kpc). We also show that the mass estimates from these methods, in the absence of X-ray spectra close to the virial radius, suffer from a degeneracy between the virial mass (M200) and the concentration parameter (c) in the form of M200c2 ≈ constant. Additionally, the lack of soft-X-ray (≲ 0.5 keV) coverage and poor spatial resolution makes us overestimate min(tcool/tff) by a factor of few in clusters with min(tcool/tff) ≲ 5. This bias can largely explain the lack of cool-core clusters with min(tcool/tff) ≲ 5.

Sarkar, Kartick C. (ORCID:0000000277678472)↗

DOE OSTI2020

Perspective on Technical Lignin Fractionation

Technical lignin extracted from pulping and biorefining processes provides a class of complex and polydisperse phenolic polymers. Preparation of lignin with lower structural complexity and polydispersity through lignin fractionation is one of the primary solutions to engineer lignin into a value-added material. Sequential lignin fraction by pH controlled precipitation from 12 to 1 is one of the primary developed methods. Partial solubility of lignin in organic solvents is another promising method for lignin fractionation. Organic solvents with different polarity and solubility factors are able to fractionate lignin, yielding a more homogeneous chemical structure. As a modification of the lignin fractionation process using solvents, water/organic solvents mixture, such as propan-2-one, alcohols, and acetic acid, from room to high temperature has been proposed as a greener method for lignin fractionation. Using membrane technology is another promising method and current results indicate a good potential for lignin recovery and fractionation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1984

Circular waveguide bifurcation for asymmetric modes

An analytical solution for a circular waveguide bifurcation with incident TE(11)- and TM(11)-modes is presented using the residue calculus method. It is shown how the coupling between the TE(1n)- and TM(1n)-modes can be taken into account by expressing the coupling factor as a contour integral, which is the key step enabling the residue calculus method to be applied. Graphical results for the scattering matrix parameters of the junction are given for a range of waveguide radii of interest in the design of dual-mode coaxial prime focus feeds for paraboloidal antennas.

Schilling, H. W.↗

NASA NTRS1985

Two dimensional and axisymmetric heat transfer results with the CSCM upwind implicit algorithm

The single level conservative supra characteristic method (CSCM-S) is an upwind implicit method that is very robust and in a single level relaxation format makes efficient use of computer resources, and is very rapidly convergent. These factors render the unconditionally stable algorithm a useful compromise between Parabolized Navier-Stokes methods and two level linearized implicit time dependent methods and, thus, the method is very attractive for multidimensional Navier-Stokes problems. In this paper the heat transfer prediction capabilities of the CSCM schemes for flat plate, nozzle, blunt cone and bluff body flows are reported for the first time. Results are compared with available experimental heat transfer measurements.

Bardina, J.↗

NASA NTRS1984

Design of power-transmitting shifts

Power transmission shafting which is a vital element of all rotating machinery is discussed. Design methods, based on strength considerations for sizing shafts and axles to withstand both steady and fluctuating loads are summarized. The effects of combined bending, torsional, and axial loads are considered along with many application factors that are known to influence the fatigue strength of shafting materials. Methods are presented to account for variable amplitude loading histories and their influence on limited life designs. The influences of shaft rigidity, materials, and vibration on the design are discussed.

Loewenthal, S. H.↗

NASA NTRS2017

Characterization of the Modal Characteristics of Structures Operating in Dense Liquid Oxygen Turbopumps

A number of valuable conclusions can be drawn from this study. First, knockdown factors for a specific fluid are not constant but instead are dependent on the mode shape, although the largest this variability gets is about 10% for LOX, the densest fluid. The factors decrease the most for lower frequency shapes and less for higher ones. It follows, therefore, that mode number mismatch between air and fluid operation becomes not only possible, but common, as a knockdown factor for a particular mode shape may be higher than for another mode shape. Since this is a function of added mass, the mismatch is more prevalent for higher density fluids, but it initiates even for very low density ones. Another important conclusion reached is that it appears that the basic mode shapes of a structure do not change if it is fully symmetric, which includes its geometry and boundary conditions. There is some indication of small changes in the relative magnitudes within the mode shape. This conclusion is evident in the results from the cantilever rectangular plate and the inducer, which are not symmetric, and the fixed-fixed plate and the annular disk, which are. For non-symmetric structures, though, the mode shapes almost universally change for dense fluids, as shown by the very low MAC calculations. For the inducer in particular, the changes follow a trend of reduced parabolic and sine wavelengths with increasing density. It is critical to recognize the change in mode shape for several reasons. First, model updating with modal test becomes problematic if the shapes change. Second, design to avoid resonance is highly critical on the mode shape for modes other than the primary ones, as resonance is only a factor when the excitation shape matches the mode shape. Finally, application of the modal superposition method of forced response analysis is dependent on the use of accurate mode shapes. A more-refined assessment of the "knockdown" factor values and ranges than any previously reported in the literature for a realistic engineering structure is also presented in this paper. This data is of tremendous benefit for preliminary analysis and design, where a quick estimate is necessary. These results are important not just for rocket engine turbomachinery, but for water pumps and turbines, propellers, and any other structure operating in a heavy fluid with dynamic excitation. The clear avenue for future work for this endeavor is to expand the analytical techniques discussed in the literature to develop analytical expressions and justification for the mode shape changes and associated frequency knockdowns. These expressions must be able to accurately predict the functional relationship to the shapes, which will enable accurate tracing of the mode number from vacuum analysis (or testing in air) to analysis and operation in the intended fluid environment.

Chiu, Joseph↗

DOE OSTI2020

A Tool for Performing Link Analysis, Operational Sequence Analysis, and Workload Analysis to Support Nuclear Power Plant Control Room Modernization

Nuclear power continues to have an imperative role for the U.S.’s electricity generation. However, for these nuclear power plants (NPPs) to remain economically viable, new strategies for reducing operations and maintenance costs must be explored. The U.S. Department of Energy Light Water Reactor Sustainability Program is researching how to digitally transform existing analog and hybrid main control rooms into a fully integrated control room that addresses this challenge. The transformation will fundamentally change the conduct of operations for these U.S. NPPs. Human factors engineering has a vital role in this effort, where traditional task analysis methods are important in informing the design of advanced human-system interface displays. This work describes a preliminary tool to support task analysis for the development of these advanced displays. Details on the use of this tool, including the specific task analysis methods offered, are presented in this paper.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1992

Analytical estimates of radial segregation in Bridgman growth from low-level steady and periodic accelerations

Approximate analytical solutions are developed that are mathematically tractable but provide the elements of CFD models for estimating convective flows subjected to low-level accelerations. The estimates are applicable to dilute systems that have horizontal temperature gradients in the vertical Bridgman configuration. The Navier-Stokes momentum equation is solved in 1D and subsequently in 2D by the first-order perturbation method. The analysis used is the case of plane-front solidification of a dilute system in the vertical thermally stable configuration. The model is found to predict the degree of radial segregation within a factor of two for a range of material and processing parameters. The method provides detailed information on the effects of processing on solute distribution in the grown crystal which are of interest in the orbital experiments emphasizing the control of radial segregation.

Naumann, Robert J.↗

DOE OSTI2023

Model-Free Approach for Profiling of Polydisperse Soft Matter Using Small Angle Scattering

A strategy for determining the size polydispersity of systems from their small angle coherent scattering is outlined. Here, using the method of moment expansion, we show that the various central moments representing the average particle size, variance of particle size, and skewness of size distribution function (SDF) for polydisperse systems can be extracted from spectral analysis without bias. When the degree of polydispersity is moderate, SDF can be further reconstructed based on the maximum entropy principle. Numerical benchmarking of a model study over a wide range of size nonuniformity demonstrates the validity of this analytical approach for quantifying the size distribution of general soft matter systems in a model-free manner. Furthermore, the efficacy of this method was validated by successfully applying it to the fitting of small-angle neutron scattering data obtained from L64 Pluronic micelles using various form factor models. The numerical and experimental verification underscores the reliability and versatility of this method in accurately characterizing the size distribution of complex soft matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Predicting transport of intra-articularly injected growth factor fusion proteins into human knee joint cartilage

There are no drugs or treatment methods known to prevent the development of post-traumatic osteoarthritis (PTOA), a type of osteoarthritis (OA) that is triggered by traumatic joint injuries and accounts for ~12% of the nearly 600 million OA cases worldwide. Lack of effective drug delivery techniques remains a major challenge in developing clinically effective treatments, but cationic delivery carriers can help overcome this challenge. Scaling up treatments that are effective in in vitro models to achieve success in preclinical in vivo models and clinical trials is also a challenging problem in the field. Here we use a cationic green fluorescent protein (GFP) as a carrier to deliver Insulin-Like Growth Factor 1 (IGF-1), a drug considered as a potential therapeutic for PTOA. GFP-IGF-1 conjugates were first synthesized as fusion proteins with different polypeptide linkers, and their transport properties were characterized in human cartilage explants. In vitro experimental data were used to develop a predictive mathematical transport model that was validated using an independent in vitro experimental data set. In this study, the model was used to predict the transport of these fusion proteins upon intra-articular injection into human knee joints. The predictions included results for the rate and extent of fusion protein penetration into cartilage, and the maximum levels of fusion proteins that would escape into systemic circulation through the joint capsule. Together, our transport measurements and model set the stage for translation of such explant culture studies to in vivo preclinical studies and potentially clinical application.

36 MATERIALS SCIENCE↗

NASA NTRS1993

A morphological filter for removing 'Cirrus-like' emission from far-infrared extragalactic IRAS fields

The presence of diffuse extended IR emission from the Galaxy in the form of the so called 'Galactic Cirrus' emission has hampered the exploration of the extragalactic sky at long IR wavelengths. We describe the development of a filter based on mathematical morphology which appears to be a promising approach to the problem of cirrus removal. The method of Greyscale Morphology was applied to a 100 micron IRAS image of the M81 group of galaxies. This is an extragalactic field which suffers from serious contamination from foreground Galactic 'cirrus'. Using a technique called 'sieving', it was found that the cirrus emission has a characteristic behavior which can be quantified in terms of an average spatial structure spectrum or growth function. This function was then used to attempt to remove 'cirrus' from the entire image. The result was a significant reduction of cirrus emission by an intensity factor of 15 compared with the original input image. The method appears to preserve extended emission in the spatially extended IR disks of M81 and M82 as well as distinguishing fainter galaxies within bright regions of galactic cirrus. The techniques may also be applicable to IR databases obtained with the Cosmic Background Explorer.

Appleton, P. N.↗

DOE OSTI2020

Lattice Physics Calculations Using the Embedded Self-Shielding Method in Polaris, Part I: Methods and Implementation

Polaris is a 2-dimensional multigroup lattice physics capability in the SCALE code system for the analysis of light water reactor fuel designs. The goal of light water reactor lattice physics codes is to generate few-group homogenized cross sections for downstream full-core nodal diffusion calculations. Additionally, lattice physics calculations contain three primary components: the cross section processing calculation, the 2D transport calculation, and the depletion calculation. This paper summarizes the calculational methods and their implementation into Polaris, with an emphasis on implementation of the embedded self-shielding method. The accuracy of the embedded self-shielding method depends on the procedure used to generate self-shielding factors on the multigroup library. Numerical benchmarks calculations reveal that the accuracy of Polaris eigenvalue predictions is enhanced by (1) using heterogeneous unit cell models to generate the self-shielding factors on the library and (2) using self-shielding factors for within-group scattering cross section.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Data reduction in deterministic neutron transport calculations using machine learning

Neutron cross section matrices for fission and scattering data are required for each material, temperature, and enrichment level to calculate the neutron transport equation accurately. Here, this information can be a limiting factor when using the multigroup discrete ordinates (S N ) method when the number of energy groups is large. Machine Learning (ML) can be used to replace the need for the cross section matrices by reproducing the function that maps the scalar flux to the scattering and fission sources. Through the use of autoencoders and Deep Jointly-Informed Neural Networks (DJINN), the data storage requirements are reduced by 94% of the original data for a 618 group problem. This is accomplished while preserving the scalar flux, maintaining generality, and decreasing wall clock times.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders

The anomalies in the high voltage converter modulator (HVCM) remain a major down time for the spallation neutron source facility, that delivers the most intense neutron beam in the world for scientific materials research. In this work, we propose neural network architectures based on Recurrent AutoEncoders (RAE) to detect anomalies ahead of time in the power signals coming from the HVCM. Bi-directional gated recurrent unit, bi-directional long-short term memory (LSTM), and convolutional LSTM (ConvLSTM) are developed, trained, and tested using real experimental signals from the HVCM module. The results show a good performance of the proposed RAE models, achieving precision up to 91%, recall up to 88%, false omission rate as low as 20% (i.e. 80% of the anomalies were detected), and area under the ROC curve up to 0.9. The three RAE models provide very comparable performance, with LSTM showing slightly better performance than GRU and ConvLSTM. The RAE models are benchmarked against other anomaly detection methods, including isolation forest, support vector machine, local outlier factor, feedforward and convolutional autoencoders, and others; showing a better performance. Here, the results of this study demonstrate the promising potential of RAE in anomaly detection for real-world power systems, and for increasing the reliability of the HVCM modules in the spallation neutron source.

42 ENGINEERING↗

DOE OSTI2024

On forced RF generation of CW magnetrons for accelerators

CW magnetrons, initially developed for industrial RF heaters, were suggested to power RF cavities of superconducting accelerators due to their higher efficiency and lower cost than traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. This causes regenerative instability with a quite large noise when a magnetron operates with the anode voltage above the threshold of self-excitation. Traditionally, an injection locking by a small signal is used for stabilization of magnetrons. In this case CW magnetrons with the injection-locked oscillations generate a high level of noise. This may preclude use of standard CW magnetrons in this operating mode in the Superconducting RF (SRF) accelerators. In this article we described a method developed for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The method is most suitable for powering high Q-factor cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Predicting the superconducting critical temperature in transition metal carbides and nitrides using machine learning

Transition metal carbides and nitrides have unique mechanical and chemical characteristics. At low temperatures many of them also exhibit superconductivity, which can be controlled by substitutions into both the transition metal and carbon/nitrogen sites. To investigate the factors governing the superconducting state, we apply machine learning methods. Here we collected a dataset containing 147 materials, which was used to create a pipeline for predicting their superconducting critical temperature. When this pipeline is applied to a randomly selected test set, it shows a good performance, with of 0.82 and RMSE of 1.9 K. To explore the limits of the machine learning approach, we also use it to predict entire substitution series within the dataset. This represents a realistic test for the predictive models, which can be extremely useful when applied to new substitutions in materials systems. The performance of the pipeline in this case is much more uneven, with good predictions for some series, while for others the model shows minimal predictive power. We discuss possible reasons for these results, as well as methods to estimate the performance of machine learning on new substitution series.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Climate change is intensifying rainfall erosivity and soil erosion in West Africa

Soil erosion is a critical environmental challenge with significant implications for agriculture, water quality, and ecosystem stability. Understanding its dynamics is essential for sustainable environmental management and societal welfare. Here, we analyze rainfall erosivity and erosion patterns across West Africa (WAF) during the historical (1982–2014), near future (2028–2060), and far future (2068–2100) periods under Shared Socioeconomic Pathways (SSPs 370 and 585). Using bias-corrected-downscaled (BCD) climate models validated against reference data, we ensure an accurate representation of rainfall—a key driver of erosivity (R-factor) and soil erosion. We compare Renard's approach and the Modified Fournier Index (MFI) to calculate the R-factor and note a strong correlation. However, Renard's method shows slightly lower accuracy in Sierra Leone, Guinea, and The Gambia, likely due to its inability to capture high-intensity, short-duration rainfall events. In contrast, the MFI, utilizing continuous rain gauge data, proves more reliable for these regions. We also attribute fluctuations in erosivity, such as those seen during the 2003 West Africa floods, to synoptic weather patterns influenced by multiple climate processes. Furthermore, our analysis reveals regions where future soil erosion could exceed 20 t/ha/yr due to climate change. Under the SSP 370 scenario, soil erosion in WAF is projected to rise by 14.84 % in the near future and 18.65 % in the far future, increasing further under SSP 585 to 19.86 % and 23.49 %, respectively. The most severe increases are expected in Benin and Nigeria, with Nigeria potentially facing a 66.41 % rise in erosion by the far future under SSP 585. These findings highlight the region's exposure to intensified climatic conditions and underscore the urgent need for targeted soil management and climate adaptation strategies to mitigate erosion's ecological and socioeconomic impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Quantification of storage required for preserving frequency security in wind‐integrated systems

Abstract The penetration of wind power generation into the power grid has been accelerated in recent times due to the aggressive emission targets set by governments and other regulatory authorities. Although wind power has the advantage of being environment‐friendly, wind as a resource is intermittent in nature. In addition, wind power contributes little inertia to the system as most wind turbines are connected to the grid via power electronic converters. These negative aspects of wind power pose serious challenges to the frequency security of power systems as penetration increases. In this work, an approach is proposed where an energy storage system (ESS) is used to mitigate frequency security issues of wind‐integrated systems. ESSs are well equipped to supply virtual inertia to the grid due to their fast‐acting nature, thus replenishing some of the energy storage capability of displaced inertial generation. In this work, a probabilistic approach is proposed to estimate the amount of inertia required by a system to ensure frequency security. Reduction in total system inertia due to the displacement of conventional synchronous generation by wind power generation is considered in this approach, while also taking into account the loss of inertia due to forced outages of conventional units. Monte Carlo simulation is employed for implementing the probabilistic estimation of system inertia. An ESS is then sized appropriately, using the system swing equation, to compensate for the lost inertia. The uncertainty associated with wind energy is modeled into the framework using an autoregressive moving average technique. Effects of increasing the system peak load and changing the wind profile on the expected system inertia are studied to illustrate various factors that might affect system frequency security. The proposed method is validated using the IEEE 39‐bus test system.

17 WIND ENERGY↗