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At least 19 records

Feasibility Study of Developing Alternative Common-Cause Failure Model for Event Assessment

This report is a revision of the original report, INL/LTD-14-33376. The original report, which was a limited distribution to the Nuclear Regulatory Commission (NRC) only and not available to the public, was revised as this report for public distribution. The report presents the feasibility study of alternative common-cause failure (CCF) models that could be used for event assessment in the Standardized Plant Analysis Risk (SPAR) models. The current CCF model used by the SPAR models is the alpha factor model. The proposed alternative CCF models are the partial alpha factor model and general dependency model. These alternative CCF models are reviewed and compared to the current alpha factor model, with the partial alpha factor model being identified as the preferred CCF model that could be used for event assessment in the SPAR models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Causal CCF Parameter Estimations 2020

This report documents the quantitative results of the causal common-cause failure (CCF) parameter estimations for the failure cause groups “component,” “design,” “environment,” “human,” and “other,” based on CCF data through 2020 in the U.S. Nuclear Regulatory Commission (NRC) CCF database: https://rads.inl.gov/Pages/CCF.aspx. This report utilizes the same data period (2006–2020) and CCF templates as INL/EXT-21-62940, Revision 1, CCF Parameter Estimations, 2020 Update. The 2015 causal CCF prior distributions for the specific failure cause groups (instead of the 2015 generic CCF prior distributions) were used in this report to estimate the associated causal CCF parameters. All the 2015 causal CCF prior distributions and generic CCF prior distributions were developed in INL/EXT-21-43723, Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors, using CCF data from 1997 to 2015. These quantitative results were developed to support the causal alpha factor model and should be used as appropriate in probabilistic risk assessment (PRA) studies such as the NRC Significance Determination Process for commercial nuclear power plants in the United States.

99 GENERAL AND MISCELLANEOUS↗

Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors

This report is a revision of the original report, INL/LTD-17-43723. Distribution of the original report was to the Nuclear Regulatory Commission (NRC) only, and the report was not made available to the public. The original report was revised as this report for public distribution. This report presents the latest update of generic prior distributions for common cause failure (CCF) alpha factors, as well as the development of new generic prior distributions for CCF causal alpha factors. The history of CCF treatment and parameter estimations is reviewed. The existing process for developing generic prior distributions is reviewed and used to develop new priors for CCF alpha factors and causal alpha factors. For causal alpha factors, different priors are developed for the five different CCF cause groups: Component (GC), Design (GD), Environment (GE), Human (GH), and Other (GO). These generic prior distributions could be used in the Standardized Plant Analysis Risk (SPAR) models for CCF parameter estimation. The issues and preliminary thoughts regarding prior distribution development are documented. Potential future work is then proposed for improving the process of developing priors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA

Although mRNA amplification is necessary for microarray analyses from limited amounts of cells and tissues, the accuracy of transcription profiles following amplification has not been well characterized. We tested the fidelity of differential gene expression following linear amplification by T7-mediated transcription in a well-established in vitro model of cytokine [tumor necrosis factor alpha (TNFalpha)]-stimulated human endothelial cells using filter arrays of 13,824 human cDNAs. Transcriptional profiles generated from amplified antisense RNA (aRNA) (from 100 ng total RNA, approximately 1 ng mRNA) were compared with profiles generated from unamplified RNA originating from the same homogeneous pool. Amplification accurately identified TNFalpha-induced differential expression in 94% of the genes detected using unamplified samples. Furthermore, an additional 1,150 genes were identified as putatively differentially expressed using amplified RNA which remained undetected using unamplified RNA. Of genes sampled from this set, 67% were validated by quantitative real-time PCR as truly differentially expressed. Thus, in addition to demonstrating fidelity in gene expression relative to unamplified samples, linear amplification results in improved sensitivity of detection and enhances the discovery potential of high-throughput screening by microarrays.

Evaluation Studies↗

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Altered TNF-Alpha, Glucose, Insulin and Amino Acids in Islets Langerhans Cultured in a Microgravity Model System

The present studies were designed to determine effects of a microgravity model system upon lipopolysaccharide (LPS) stimulated tumor necrosis factor alpha (TNF-alpha) activity and indices of insulin and fuel homeostasis of pancreatic islets of Langerhans. Islets (1726+/-1 17,150 u IEU) from Wistar Furth rats were treated as: 1) HARV (High Aspect Ratio Vessel cell culture) , 2) HARV plus LPS, 3) static culture, 4) static culture plus LPS. TNF-alpha (L929 cytotoxicity assay) was significantly increased in LPS-induced HARV and static cultures, yet the increase was more pronounced in the static culture group (p<0.05). A decrease in insulin concentration was demonstrated in the LPS stimulated HARV culture (p<0.05). We observed a greater glucose concentration and increased disappearance of arginine in islets cultured in HARVs. While nitrogenous compound analysis indicated a ubiquitous reliance upon glutamine in all experimental groups, arginine was converted to ornithine at a two-fold greater rate in the islets cultured in the HARV microgravity model system (p<0.05). These studies demonstrate alterations in LPS induced TNF-alpha production of pancreatic islets of Langerhans, favoring a lesser TNF activity in the HARV. These alterations in fuel homeostasis may be promulgated by gravity averaged cell culture methods or by three dimensional cell assembly.

Tobin, Brian W.↗

Simultaneous measurements of the hydrogen airglow emissions of Lyman alpha, Lyman beta, and Balmer alpha.

Comparison of Lyman-alpha, 740- to 1050-A, and Balmer-alpha airglow measurements made at 134 deg solar-zenith angle on Oct. 13, 1969, with resonance-scattering models of solar radiation. Model comparison with Lyman-alpha data fixes the hydrogen column abundance over 215 km to 2 x 10 to the 13th per cu cm within a factor of 2. Differences between the Lyman-alpha model and data indicate a polar-equatorial departure from spherical symmetry in the hydrogen distribution. A Lyman-beta model based on the hydrogen distribution found to fit the Lyman-alpha data fits the spatial variation of the 740- to 1050-A data well from 100 to 130 km, but it does not fit the data well at higher altitudes; thus the presence of more rapidly absorbed shorter-wavelength radiation is indicated. This same resonance-scattering model yields Balmer-alpha intensities that result in good spatial agreement with the Balmer-alpha measurements, but a fivefold increase in the measured solar line center Lyman-beta flux is required (as required for the Lyman-beta measurement). The intensity ratio of Lyman-beta and Balmer-alpha at night is found to be a simple measure of the hydrogen optical depth if measurements with good accuracy can be made in the visible and ultraviolet spectrum.

Weller, C. S.↗

A Mathematical Model of the Dynamics of Cytokine Expression and Human Immune Cell Activation in Response to the Pathogen Staphylococcus aureus

Cell-based mathematical models have previously been developed to simulate the immune system in response to pathogens. Mathematical modeling papers which study the human immune response to pathogens have predicted concentrations of a variety of cells, including activated and resting macrophages, plasma cells, and antibodies. This study aims to create a comprehensive mathematical model that can predict cytokine levels in response to a gram-positive bacterium, S. aureus by coupling previous models. To accomplish this, the cytokines Tumor Necrosis Factor Alpha (TNF-α), Interleukin 6 (IL-6), Interleukin 8 (IL-8), and Interleukin 10 (IL-10) are included to quantify the relationship between cytokine release from macrophages and the concentration of the pathogen, S. aureus, ex vivo. Partial differential equations (PDEs) are used to model cellular response and ordinary differential equations (ODEs) are used to model cytokine response, and interactions between both components produce a more robust and more complete systems-level understanding of immune activation. In the coupled cellular and cytokine model outlined in this paper, a low concentration of S. aureus is used to stimulate the measured cellular response and cytokine expression. Results show that our cellular activation and cytokine expression model characterizing septic conditions can predict ex vivo mechanisms in response to gram-negative and gram-positive bacteria. Our simulations provide new insights into how the human immune system responds to infections from different pathogens. Novel applications of these insights help in the development of more powerful tools and protocols in infection biology.

60 APPLIED LIFE SCIENCES↗

Using Lunar Module Shadows To Scale the Effects of Rocket Exhaust Plumes

Excavating granular materials beneath a vertical jet of gas involves several physical mechanisms. These occur, for example, beneath the exhaust plume of a rocket landing on the soil of the Moon or Mars. We performed a series of experiments and simulations (Figure 1) to provide a detailed view of the complex gas-soil interactions. Measurements taken from the Apollo lunar landing videos (Figure 2) and from photographs of the resulting terrain helped demonstrate how the interactions extrapolate into the lunar environment. It is important to understand these processes at a fundamental level to support the ongoing design of higher fidelity numerical simulations and larger-scale experiments. These are needed to enable future lunar exploration wherein multiple hardware assets will be placed on the Moon within short distances of one another. The high-velocity spray of soil from the landing spacecraft must be accurately predicted and controlled or it could erode the surfaces of nearby hardware. This analysis indicated that the lunar dust is ejected at an angle of less than 3 degrees above the surface, the results of which can be mitigated by a modest berm of lunar soil. These results assume that future lunar landers will use a single engine. The analysis would need to be adjusted for a multiengine lander. Figure 3 is a detailed schematic of the Lunar Module camera calibration math model. In this chart, formulas relating the known quantities, such as sun angle and Lunar Module dimensions, to the unknown quantities are depicted. The camera angle PSI is determined by measurement of the imaged aspect ratio of a crater, where the crater is assumed to be circular. The final solution is the determination of the camera calibration factor, alpha. Figure 4 is a detailed schematic of the dust angle math model, which again relates known to unknown parameters. The known parameters now include the camera calibration factor and Lunar Module dimensions. The final computation is the ejected dust angle, as a function of Lunar Module altitude.

Source record↗

Validation of the two-region Rossi-alpha model for reflected assemblies

Nuclear criticality safety, nonproliferation and safeguards, emergency response, and stockpile stewardship utilize estimates of the k eff multiplication factor. The value of k eff cannot be directly measured, but it can be inferred from the prompt neutron period. One modality of measuring the prompt neutron period is the Rossi-alpha method, which is predicated on fitting a histogram of detection time differences due to the nonrandom temporal distribution of same-fission-chain neutrons. Recent works have developed the motivation and theory to expand traditional one-region point kinetic models resulting in one-exponential histogram fits to two-region models that result in two-exponential fits. This paper validates the new two-region model using organic scintillator measurements of copper-reflected weapons-grade plutonium (0:83 ≤ k eff ≤ 0:94) and high-density- polyethylene-reflected highly enriched uranium (0:73 ≤ k eff ≤ 0:95). Furthermore, the results show that more thermal systems have shorter prompt neutron periods in the core region due to increased induced-fission probabilities for moderated neutrons. Here, a new parameter introduced by the two- region model is also shown to be correlated to the amount of reflection, and may be used to infer assembly properties such as type and amount of reflector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Theoretical emergent Lyman alpha intensities from Mars.

The behavior of the Lyman alpha 1216-A intensity on Mars is presented for a range of atomic hydrogen density distributions below 200 km. Two sets of radiative transfer calculations have been performed. The first is based on spherical geometry and includes the effect of pure absorption of the resonance photons by CO2. The second set is based on the simpler plane parallel geometry and includes the effects of both pure absorption and a varying Doppler width associated with the planetary Lyman alpha line. From the plane parallel solutions, we are able to estimate and account for the effect of a varying Doppler width on our spherical model results. When pure absorption and a varying Doppler width are incorporated in the theory, the maximum change in the Lyman alpha disc intensity is a factor of about 2 over the range of hydrogen density models considered.

Strickland, D. J.↗

Transient modeling/analysis of hyperbolic heat conduction problems employing mixed implicit-explicit alpha method

This paper describes the evaluation of mixed implicit-explicit finite element formulations for hyperbolic heat conduction problems involving non-Fourier effects. In particular, mixed implicit-explicit formulations employing the alpha method proposed by Hughes et al. (1987, 1990) are described for the numerical simulation of hyperbolic heat conduction models, which involves time-dependent relaxation effects. Existing analytical approaches for modeling/analysis of such models involve complex mathematical formulations for obtaining closed-form solutions, while in certain numerical formulations the difficulties include severe oscillatory solution behavior (which often disguises the true response) in the vicinity of the thermal disturbances, which propagate with finite velocities. In view of these factors, the alpha method is evaluated to assess the control of the amount of numerical dissipation for predicting the transient propagating thermal disturbances. Numerical test models are presented, and pertinent conclusions are drawn for the mixed-time integration simulation of hyperbolic heat conduction models involving non-Fourier effects.

Tamma, Kumar K.↗

Predicting Ly-alpha intensities in coronal streamers

SOHO (Solar and Heliospheric Observatory) UVCS (Ultraviolet Coronagraph Spectrometer) will make long term observations of coronal streamers in UV lines, providing a new tool for the analysis of structures which have been known for decades but are still far from being adequately described. Work to evaluate the Lyman alpha brightness of coronal streamers is reported, adopting the streamer models obtained, via a time dependent numerical relaxation technique. This will yield understanding on the role of geometric versus physical factors in determining the streamer lyman alpha intensity and provide guidelines for UVCS observational operations. Future prospects along this line of research are summarized.

Noci, Giancarlo↗

Light-Curve Modelling Constraints on the Obliquities and Aspect Angles of the Young Fermi Pulsars

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed gamma-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity alpha and of the line of sight angle zeta, yielding estimates of the radiation beaming factor and radiated luminosity. Using different gamma-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit gamma-ray light curves for 76 young or middle-aged pulsars and we jointly fit their gamma-ray plus radio light curves when possible. We find that a joint radio plus gamma-ray fit strategy is important to obtain (alpha, zeta) estimates that can explain simultaneously detectable radio and gamma-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (alpha, gamma) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the gamma-ray only fit leads to underestimated alpha or zeta when the solution is found to the left or to the right of the main alpha-zeta plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favored in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived gamma-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between gamma-ray luminosity and spin-down power is consistent with a square root dependence. The gamma-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.

neutron aEuro" pulsars:↗

Consequences of contamination of the spacecraft environment: immunologic consequences

Long-term space voyages pose numerous known and unknown health hazards, to the human immune system. Well-studied clinical examples of secondary immunodeficiencies created on Earth, lead one to predict that the conditions of prolonged space flight would weaken the human immune responses that normally hold infection and cancer in check. From evidence gathered from humans flown for prolonged periods in space and from human models of space flight studied on Earth it is reasonable to suspect that space travelers to the planet Mars would experience a weakening of immunity. Subtle defects of immune cell structure and function have been observed in astronauts, such as weakening of specific T-lymphocyte recall of specific antigens. Ground-based models also have demonstrated alterations of immune function, such as the elevation of neuroendocrine immune system messengers, interleukin-6, and soluble tumor necrosis factor-alpha receptor in sleep deprivation. Since severe immune compromise the clinical consequences of reactivation of latent virus infections and the development of cancer, has yet to be seen in space flight or in the Earth models, it is extremely important to begin to quantify early changes in immunity to predict the development of immune system collapse with poor clinical outcomes. This approach is designed to validate a number of surrogate markers that will predict trouble ahead. Inherent in this research is the development of countermeasures to reduce the risks of infection and cancer in the first humans going to Mars.

Non-NASA Center↗

Three-dimensional CTOA and constraint effects during stable tearing in a thin-sheet material

A small strain theory, three-dimensional elastic-plastic finite element analysis was used to simulate fracture in thin sheet 2024-T3 aluminum alloy in the T-L orientation. Both straight and tunneled cracks were modeled. The tunneled crack front shapes as a function of applied stress were obtained from the fracture surface of tested specimens. The stable crack growth behavior was measured at the specimen surface as a function of applied stress. The fracture simulation modeled the crack tunneling and extension as a function of applied stress. The results indicated that the global constraint factor, alpha(sub g), initially dropped during stable crack growth. After peak applied stress was achieved, alpha(sub g) began to increase slightly. The effect of crack front shape on alpha(sub g) was small, but the crack front shape did greatly influence the local constraint and through-thickness crack-tip opening angle (CTOA) behavior. The surface values of CTOA for the tunneled crack front model agreed well with experimental measurements, showing the same initial decrease from high values during the initial 3mm of crack growth at the specimen's surface. At the same time, the interior CTOA values increased from low angles. After the initial stable tearing region, the CTOA was constant through the thickness. The three-dimensional analysis appears to confirm the potential of CTOA as a two-dimensional fracture criterion.

Dawicke, D. S.↗

Improving the feasibility of economical proton-boron-11 fusion via alpha channeling with a hybrid fast and thermal proton scheme

The proton-boron-11 (p-B11) fusion reaction is much harder to harness for commercial power than the easiest fusion reaction, namely, the deuterium and tritium (DT) reaction. The p-B11 reaction requires much higher temperatures, and, even at those higher temperatures, the cross section is much smaller. However, as opposed to tritium, the reactants are both abundant and nonradioactive. It is also an aneutronic reaction, thus avoiding radioactivity-inducing neutrons. Economical fusion can only result, however, if the plasma is nearly ignited; in other words if the fusion power is at least nearly equal to the power lost due to radiation and thermal conduction. Because the required temperatures are so high, ignition is thought barely possible for p-B11, with fusion power exceeding the bremsstrahlung power by only around 3%. We show that there is a high upside to changing the natural flow of power in the reactor, putting more power into protons, and less into the electrons. This redirection can be done using waves, which tap the alpha particle power and redirect it into protons through alpha channeling. Using a simple power balance model, we show that such channeling could reduce the required energy confinement time for ignition by a factor of 2.6 when energy is channeled into thermal protons, and a factor of 6.9 when channeled into fast protons near the peak of the reactivity. Furthermore, alpha channeling could dramatically improve the feasibility of economical p-B11 fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Genetic tools for engineering Zymomonas mobilis , Cereibacter sphaeroides and Novosphingobium aromaticivorans to improve production of bioenergy compounds

Limited genetic tools for non-model bacteria are one of the limiting factors for genetic studies. This review compiles genetic tools used for three non-model alpha-proteobacteria, such as Zymomonas mobilis, Cereibacter (Rhodobacter) sphaeroides, and Novosphingobium aromaticivorans, which hold significant potential to produce industrially essential bioenergy compounds due to their distinctive metabolic pathways and resilience in extreme environments. Each of these strains has a unique genetic profile that enables them to efficiently carry out key reactions relevant to producing bioenergy compounds, such as converting sugars into bioenergy compounds and breaking down lignotoxins. Genetic tools can further optimize these strains for enhanced bioenergy compound production. This review explores the metabolic advantages of these organisms. It highlights the available array of genetic toolkits that can be shared among them to unlock their full potential for sustainable biofuel production.

Biofuel↗