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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Smoothing Lexis diagrams using kernel functions: A contemporary approach

Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc. Inevitably the amount of information per Lexis diminishes with increasing stratification. Several methods have been proposed to smooth observed Lexis diagrams up front to clarify salient patterns and improve summary estimates of averages, gradients, and trends. In this article, we develop a novel bivariate kernel-based smoother that incorporates two key innovations. First, for any given kernel, we calculate its singular values decomposition, and select an optimal truncation point—the number of leading singular vectors to retain—based on the bias-corrected Akaike information criterion. Second, we model-average over a panel of candidate kernels with diverse shapes and bandwidths. The truncated model averaging approach is fast, automatic, has excellent performance, and provides a variance-covariance matrix that takes model selection into account. We present an in-depth case study (invasive estrogen receptor-negative breast cancer incidence among non-Hispanic white women in the United States) and simulate operating characteristics for 20 representative cancers. The truncated model averaging approach consistently outperforms any fixed kernel. Our results support the routine use of the truncated model averaging approach in descriptive studies of cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Human-Centered and Explainable Artificial Intelligence in Nuclear Operations

Nuclear power plants in the United States are critical to the nation’s energy security, accounting for 20% of all electricity produced for the power grid. As energy needs grow, 100 gigawatts of additional nuclear power will be necessary by 2050, more than double the current capacity. Realizing this target requires cutting-edge technology like artificial intelligence (AI) and machine learning (ML) that can bring about significant increases in the level of automation. Human-centered AI (HCAI) is a combination of human-centered design (human factors, human-in-the-loop, etc.) with AI/ML to help produce an efficient and reliable system with full consideration for human engagement. This paper provides a comprehensive and novel discussion of HCAI considerations in nuclear power, introducing unique applications for the existing fleet as well as new advanced reactor designs. We include real-life use cases of AI applications to work management processes at nuclear power sites and highlight lessons learned for HCAI.

Hall, Anna↗
DOE OSTI2022

Current state and future trends in boundary layer control on lifting surfaces

Successful flow control may bring numerous benefits, such as flow stabilization, flow reattachment, separation delay, drag reduction, lift increase, aerodynamic performance improvement, energy efficiency increase, shock delay or weakening, noise reduction, etc. For these purposes, many different flow control devices, which can be classified as passive, semi-active and active, have been designed and tested. This review paper aims to highlight the most promising and commonly employed boundary layer control methods as well as outline their potential in specific applications in aerospace and energy engineering. Referenced studies, performed on various geometries (flat plates, channels, airfoils, wings, blades, cylinders), are primarily numerical or experimental. Although enhanced aerodynamic performance is achieved in many cases, further research is required to draw general conclusions. This paper aims to demonstrate that, in the future, we may expect further developments of flow control actuators, as well as their increased application.

42 ENGINEERING↗
DOE OSTI2022

Multi-process tooling for discontinuous carbon and hybrid glass fiber thermoplastics

Expensive tooling often constraints the use of composites in the design and development of automotive parts. While there is significant confidence and knowledge in sheet and bulk metals, composite processes are less understood in mass production environment. The processes used to produce composites and resulting properties are influenced by fiber length attrition, resin to fiber ratio, process waste etc. Tool designs are determined very early in the engineering process. It is cost prohibitive to build additional tools, in the event it becomes obvious a better processing method and material would be beneficial, the original decision is not easily changed. In the present work we recognize the bottleneck of tooling costs and provide an approach of multi-process tooling. The innovation of this work is the design and demonstration of a single tool for different processes namely injection, injection-compression and extrusion-compression. The materials used in this study were long and short fiber thermoplastics (LFTs and SFTs). The resulting structure-property relationships have been reported for the materials and processing methods with a battery tray (BT) tool.

Vaidya, Uday↗
DOE OSTI2022

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Scalable production of recombinant three-finger proteins: from inclusion bodies to high quality molecular probes

The three-finger proteins are a collection of disulfide bond rich proteins of great biomedical interests. Scalable recombinant expression and purification of bioactive three-finger proteins is quite difficult. We introduce a working pipeline for expression, purification and validation of disulfide-bond rich three-finger proteins using E. coli as the expression host. With this pipeline, we have successfully obtained highly purified and bioactive recombinant α-Βungarotoxin, k-Bungarotoxin, Hannalgesin, Mambalgin-1, α-Cobratoxin, MTα, Slurp1, Pate B etc. Milligrams to hundreds of milligrams of recombinant three finger proteins were obtained within weeks in the lab. The recombinant proteins showed specificity in binding assay and six of them were crystallized and structurally validated using X-ray diffraction protein crystallography. Our pipeline allows refolding and purifying recombinant three finger proteins under optimized conditions and can be scaled up for massive production of three finger proteins. As many three finger proteins have attractive therapeutic or research interests and due to the extremely high quality of the recombinant three finger proteins we obtained, our method provides a competitive alternative to either their native counterparts or chemically synthetic ones and should facilitate related research and applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2023

Procedure for locating oil and gas wells in the Appalachian Basin

Locating undocumented (or poorly documented) oil and gas wells for environmental assessment is often difficult. Remnant features that confirm the presence of a well (intact casing/wellhead, well bore, etc.) are typically less than a meter in size and often are obscured from direct observation on the ground or from the air (by dense vegetation, for example). To efficiently find such features, it is useful to first systematically compile publicly available digital data at progressively smaller scales prior to embarking on field campaigns. Further, the information presented here describes the procedure developed and used by the U.S. Department of Energy's National Energy Technology Laboratory to locate potential oil and gas well sites for follow-up field verification and characterization. Digital data are first compiled from national and state resources such as well location/production databases, historical topographic maps, historical aerial photographs, and LiDAR data. Although each data set is likely to be incomplete or inaccurate to some extent, combining the data resources using geographic information system technology can generate potential well site targets with a higher degree of confidence, which improves the efficiency of fieldwork activities. This workflow was developed in the Appalachian Basin region, and although certain aspects may be unique, the general process would be applicable to locating undocumented wells in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data for Catalyst and Reactor Design Considerations for Selective Production of Acids by Oxidative Cleavage of Alkenes with H2O2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η2-O2) complexes vs. H2O2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H2O2 concentrations. Semi-batch reactors with continuous introduction of H2O2 solutions offer the means to maintain low H2O2 concentrations while providing sufficient quantities of H2O2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. This kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H2O2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H2O2 feed rate increases selectivity towards oxidative cleavage products and selective use of H2O2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semi-batch reactors with optimized molar feed rates of H2O2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H2O2 selectivity (3% to 30%). In addition, semi-batch reaction conditions used avoid H2O2-mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H2O2.

Catalysis↗
DOE OSTI2024

Process and control variables from the mercury loop at the SNS's mercury target

Set of process and control variables corresponding to the mercury process loop at the Spallation Neutron Source's (SNS) mercury target. The data corresponds to 36 measurement signals (pressure, temperature, flows, valve position, etc.) spanning from 2017/01/01 to 2023/12/31. Each signal is broken intro three-month intervals, resulting in a total of 28 files per signal during the aforementioned period of time.

mercury loop↗
DOE OSTI2025

Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

We investigated blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (poly(MTFSI)Li) at varying molar ratios to gain a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. This dataset contains the raw numerical data corresponding to the figures in the manuscript. The data files include the following information: (1) Experimental Data – includes X-ray and neutron scattering measurements, broadband dielectric spectroscopy (BDS) data, extracted DC conductivity values, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) results, extracted glass transition temperatures, etc. (2) CGMD Data – includes molecular dynamics (MD) trajectory files and computed structural correlations. All data files are organized/named according to the figure numbers in the manuscript.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On-the-fly response function generation method for composite coarse mesh

The hybrid stochastic deterministic transport code COMET, based on the incident response expansion theory, is used to model reactor cores with high fidelity and formidable computational speed. COMET models a reactor core using a library of incident flux response expansion coefficients that are pre computed for all the unique lattice cells (e.g., fuel assemblies, reflector blocks, etc.) in the core. In order to further improve its computational efficiency in pre-calculating the response library a new response function generation method is developed to compute the response functions for the composite coarse meshes made of a smaller set of unique lattices on the fly within the COMET's deterministic transport core sweep. The efficiency is achieved by eliminating a number of unique lattices that can be made up from the reduced set of unique meshes on the fly. The numerical process consists of the following steps. First, the boundary condition on composite coarse mesh boundaries is projected onto the expansion basis to compute the incident flux moments on external surfaces of all the basic (reduced set of unique) coarse meshes. Secondly, the deterministic sweeping solver in COMET is used to converge on the outgoing/incoming flux expansion moments crossing interfaces between the basic coarse meshes. Thirdly, the response functions for the composite coarse meshes are constructed as a superposition on the fly. The new response function generation method was tested on 88 composite coarse meshes consisting of CANDU fuel bundles and moderator blocks. It was found that response functions generated by the new method agree very well with those generated by direct Monte Carlo calculations. The average and maximum relative differences in the surface-to-surface response coefficients computed by the two methods are 0.10% and 0.20%, respectively. Similarly, the average and maximum relative differences in the response fission densities are 0.13% and 0.43%, respectively. These discrepancies are within one standard deviation of the stochastic uncertainties. The new method is five times faster than the original direct Monte Carlo method. The size of the response function library for the new method is five times smaller than that for the original method, leading to significantly less requirement for the computer hard drive space and memory. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Development of Cable Aging Acceptance Criteria for Nuclear Facilities

The aging of nuclear power plant electrical cables has been the subject of substantial research and development (R&D) projects in the nuclear industry, national and international laboratories, universities, and vendor organizations for several years. More specifically, these R&D efforts were conducted to develop equipment and techniques for assessing age-related degradation of in-service cables in nuclear facilities including power plants, research reactors, waste facilities and fuel fabrication plants. In recent years, cable R&D efforts in the nuclear arena have also included work to develop new cables for the next generation of reactors. Over time, exposure to harsh environmental conditions such as elevated temperatures, radiation, and humidity in nuclear installations can result in age-related degradation and failure of cables. In the current fleet of nuclear reactors, there are thousands of miles of cabling installed in each plant and many of these cables are exposed to these harsh environmental conditions. For these cables, the jacket and insulation polymers harden and become brittle over time, making them more susceptible to crack formation and growth, moisture intrusion, and other mechanisms that can lead to cable failure. Moreover, the existing U.S. fleet of 98 nuclear reactors has an average operating age of 38 years. Many of these nuclear power plants have applied for and almost all have been granted regulatory approval for license renewals to operate for 60 years, 20 years beyond their original 40-year life. Further, subsequent license renewals (SLRs) are underway with a few commercial nuclear power sites already approved to operate up to 80 years. As these reactors pursue operating life extensions, utilities must find a way to address issues associated with age-related degradation of cables. Designers of small modular reactors are also in need of technologies to evaluate the performance of cables that will be installed in harsher environments (e.g. higher temperatures, radiation doses, dose rates, etc.) than those present in current-generation reactors. Today, a variety of cable condition monitoring (CM) techniques have been developed and successfully used in nuclear facilities. These techniques are used to identify age-related degradation and assess the condition of cables to determine if their performance characteristics have changed with age. However, objective criteria must be developed for these CM tests to help quantify cable condition and thereby develop repair and replacement schedules. With operating life extending to 80 years and more SLRs on the horizon, both nuclear facilities and regulators need an objective means to determine the aged condition of cables.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optical versus radiographic imaging and tomography: introduction to the ROADS feature issue

Optical imaging is an ancient branch of imaging dating back to thousands of years. Radiographic imaging and tomography (RadIT), including the first use of X-rays by Wilhelm Röntgen, and then, $γ$ -rays, energetic charged particles, neutrons, etc. are about 130 years young. The synergies between optical and radiographic imaging can be cast in the framework of these building blocks: Physics, Sources, Detectors, Methods, and Data Science, as described in Appl. Opt. 61, RDS1 (2022). Optical imaging has expanded to include three-dimensional (3D) tomography (including holography), due in to part the invention of optical (including infrared) lasers. RadIT are intrinsically 3D because of the penetrating power of ionizing radiation. Both optical imaging and tomography (OIT) and RadIT are evolving into even higher dimensional regimes, such as time-resolved tomography (4D) and temporarily and spectroscopically resolved tomography (4D + ). Further advances in OIT and RadIT will continue to be driven by desires for higher information yield, higher resolutions, and higher probability models with reduced uncertainties. Synergies in quantum physics, laser-driven sources, low-cost detectors, data-driven methods, automated processing of data, and artificially intelligent data acquisition protocols will be beneficial to both branches of imaging in many applications. These topics, along with an overview of the Radiography, Applied Optics, and Data Science virtual feature issue, are discussed here.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Network upgrade exploiting multi band: S- or E-band?

Nowadays, the fiber spectrum is only partially exploited, i.e., mainly in the C-band and more recently in the C + L-band, where the fiber attenuation profile experiences the minimum. Thus, fiber communications technology—amplifiers, switching, transceivers, etc.—and networking solutions are mature for those spectrum bands. However, the continuous increase in traffic means that capacity saturation of the current infrastructure is looming. Taking advantage of the unused portions of the spectrum (e.g., the S- and E-bands) may be an efficient solution to accommodate an increase in traffic without installing new fibers. Research is thus investigating multi-band transmission and networking to evaluate and enable such network upgrades. Some issues need to be solved or taken into account, from the enabling technology (e.g., amplifiers in the S- or E-band are still under development) to physical layer effects previously neglected, such as stimulated Raman scattering (SRS). SRS affects wideband transmission, potentially degrading active channels. The contribution of this paper is the investigation of network upgrades for C + L-band systems. In particular, upgrades exploiting the E- and S-bands are compared taking into account each band capacity and the effects of SRS on both new and already deployed channels (in both the C- and L-bands). A detailed analysis of the physical layer is provided also in the presence of guard bands between previously exploited bands and the bands used for upgrade. By leveraging the physical layer assessment, a networking analysis is carried out to evaluate the supported traffic increase and also the signal quality degradation due to SRS on active channels. Overall, the results suggest that upgrades to the E- and S-bands support a comparable increase in traffic. However, the exploitation of the E-band with 14 THz of guard band between the C- and E-bands may avoid detrimental effects to already active channels in the C + L-band, suggesting this upgrade strategy can be the most effective of the two.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Optics-on-a-chip for ultrafast manipulation of 350-MHz hard x-ray pulses

Microelectromechanical systems (MEMS) are miniature devices integrated into a vast range of industrial and consumer applications. Optical MEMS are developed for dynamic spatiotemporal control in lightwave manipulation and communication as modulators, switches, multiplexers, spectrometer, etc. However, they have not been shown to function similarly in sub-nm wavelength regimes, namely, with hard x-rays, as high-brilliance pulsed x-rays have proven powerful for addressing challenges in time-domain science, from energy conversion to neurobiological control. While desirable temporal properties of x-ray pulses can be enhanced by optics, conventional x-ray optics are inherently massive in size, hence, never dynamic. We demonstrate highly ultrafast x-ray optics-on-a-chip based on MEMS capable of modulating hard x-ray pulses exceeding 350 MHz, 10 3 × higher than any other mechanical modulator, with a pulse purity >10 6 without compromising the spectral brilliance. Moreover, the timing characteristics of the devices can be tuned on-the-fly to deliver optimal pulse properties to create a host of dynamic x-ray instruments and applications, impossible with traditional optics of 10 9 × bulkier and more massive. The advent of the ultrafast optics-on-a-chip heralds a new paradigm of x-ray photonics, time-domain science, and accelerator diagnostics, especially at not only the future-generation light sources that offer coherent and high-frequency pulses but also lab-based facilities that normally do not offer timing structures.

42 ENGINEERING↗