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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Space Propulsion Hazards Analysis Manual (SPHAM), volume 1

The Space Propulsion Hazards Analysis Manual (SPHAM) is a compilation of methods and data directed at hazards analysis and safety for space propulsion and associated vehicles, but broadly applicable to other environments and systems. Methods are described of compiling relevant regulatory documentation, deriving design requirements and specifications, modeling accident scenarios in formal risk assessments, and correlation real-time data to risk probability modeling. Also, SPHAM provides methods for predicting post-accident blast, fragmentation, thermal, and environmental damage. Included in the appendices are an exhaustive bibliography, hazardous properties information on selected space propulsion commodities, and system descriptions of various launch vehicles, upper stages, and spacecrafts.

Becker, Dorothy L.↗

Morphologic differentiation of colon carcinoma cell lines HT-29 and HT-29KM in rotating-wall vessels

A new low shear stress microcarrier culture system has been developed at NASA's Johnson Space Center that permits three-dimensional tissue culture. Two established human colon adenocarcinoma cell lines, HT-29, an undifferentiated, and HT-29KM, a stable, moderately differentiated subline of HT-29, were grown in new tissue culture bioreactors called Rotating-Wall Vessels (RWVs). RWVs are used in conjunction with multicellular cocultivation to develop a unique in vitro tissue modeling system. Cells were cultivated on Cytodex-3 microcarrier beads, with and without mixed normal human colonic fibroblasts, which served as the mesenchymal layer. Culture of the tumor lines in the absence of fibroblasts produced spheroidlike growth and minimal differentiation. In contrast, when tumor lines were co-cultivated with normal colonic fibroblasts, initial growth was confined to the fibroblast population until the microcarriers were covered. The tumor cells then commenced proliferation at an accelerated rate, organizing themselves into three-dimensional tissue masses that achieved 1.0- to 1.5-cm diameters. The masses displayed glandular structures, apical and internal glandular microvilli, tight intercellular junctions, desmosomes, cellular polarity, sinusoid development, internalized mucin, and structural organization akin to normal colon crypt development. Differentiated samples were subjected to transmission and scanning electron microscopy and histologic analysis, revealing embryoniclike mesenchymal cells lining the areas around the growth matrices. Necrosis was minimal throughout the tissue masses. These data suggest that the RWV affords a new model for investigation and isolation of growth, regulatory, and structural processes within neoplastic and normal tissue.

Colonic Neoplasms/pathology↗

Improving Dose Modeling With Dynamic Modeling Tools [Slides]

Utilities aiming for higher fuel enrichment for power uprates or extended operation times before refueling must conduct a new dose analysis. Current conservative dose estimation standards may cause utilities to exceed regulatory limits for proposed increased fuel enrichment. A more accurate modeling of doses from reactor accidents can lower these conservative assumptions. Prescott et al. (2022) demonstrated that the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) software tool, developed at Idaho National Laboratory (INL), can be coupled with the Modular Accident Analysis Program (MAAP5) for dynamic accident analysis in reactor plants. EMRALD forms models of potential accident scenarios, while MAAP5 simulates the accident progression and dose consequences. By integrating these software tools with utility-specific data, a more precise estimation of dose consequences from plant accidents can be achieved. Preliminary findings indicate that EMRALD provides accurate mean core damage frequencies for generalized accident scenarios. Future work includes expanding the model to account for plant-specific data and mitigation factors.

97 - MATHEMATICS AND COMPUTING↗

Demonstrating the Value of 3D Models to Support Large-Scale Digital Modifications at Nuclear Power Plants

Many Nuclear Power Plants are currently in the process of extending their operating licenses for continued generation. The use of three-dimensional (3D) modeling in the early stages of large scale NPP modernization efforts is one lower cost method that can verify proposed design changes against established guidelines and allows for visual presentation of the 3D model to various stakeholders in the project. Guidance from Nuclear Regulatory Commission NUREG 0711 and 0700, and other sources on performing HF/E for control rooms and design modifications can be visually represented in 3D models. Distance and measurements, workstation design, anthropometric considerations, and early feedback of modifications are used in 3D models to identify potential human issues early in the design process. 3D modeling is a useful tool for early design and help to reduce costs and present visuals to stakeholders early in the design.

3D Models↗

Time-dependent oral absorption models

The plasma concentration-time profiles following oral administration of drugs are often irregular and cannot be interpreted easily with conventional models based on first- or zero-order absorption kinetics and lag time. Six new models were developed using a time-dependent absorption rate coefficient, ka(t), wherein the time dependency was varied to account for the dynamic processes such as changes in fluid absorption or secretion, in absorption surface area, and in motility with time, in the gastrointestinal tract. In the present study, the plasma concentration profiles of propranolol obtained in human subjects following oral dosing were analyzed using the newly derived models based on mass balance and compared with the conventional models. Nonlinear regression analysis indicated that the conventional compartment model including lag time (CLAG model) could not predict the rapid initial increase in plasma concentration after dosing and the predicted Cmax values were much lower than that observed. On the other hand, all models with the time-dependent absorption rate coefficient, ka(t), were superior to the CLAG model in predicting plasma concentration profiles. Based on Akaike's Information Criterion (AIC), the fluid absorption model without lag time (FA model) exhibited the best overall fit to the data. The two-phase model including lag time, TPLAG model was also found to be a good model judging from the values of sum of squares. This model also described the irregular profiles of plasma concentration with time and frequently predicted Cmax values satisfactorily. A comparison of the absorption rate profiles also suggested that the TPLAG model is better at prediction of irregular absorption kinetics than the FA model. In conclusion, the incorporation of a time-dependent absorption rate coefficient ka(t) allows the prediction of nonlinear absorption characteristics in a more reliable manner.

Non-NASA Center↗

Alabama Carbon Storage: Bringing Data to the People

The Gulf Coastal Plain of Alabama has proven potential for geologic carbon storage and current interest in the area for large carbon capture and storage (CCS) projects is high. Extensive CCS relevant data exist in the records of the Geological Survey of Alabama and State Oil and Gas Board of Alabama, however, most of this data is not publicly available or is scattered in separate databases, file cabinets, and tables in publications. The “Alabama Carbon Storage: Data Sharing and Engagement” (ACS-DSE) project seeks to accelerate the responsible development of large CCS projects in the Gulf Coastal Plain of Alabama and offshore in state waters through a publicly accessible database of geologic carbon storage models and data across the region. The ACS-DSE draws on the over 150 years of geologic research and over 20 years of experience in CCS research to place relevant geologic, geophysical, and infrastructure data on a single web platform. Datasets available will include formation depths and elevations, geologic structures, reservoir properties, digital well logs (LAS files), existing penetrations, and geologic models. In addition to downloadable datasets, links to CCS related regulatory agencies and other sources of information will be included (for example, Class VI UIC permitting regulations and pipeline regulations). By making these datasets and models available in commonly used formats on a public website, the project will increase transparency in decision making and decrease the data acquisition time for industry.

01 COAL, LIGNITE, AND PEAT↗

Detection of "noisy" chaos in a time series

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Non-NASA Center↗

Protocol for applying a network-enabled gene discovery pipeline to non-model plant species

Identifying upstream regulators of key genes is essential for understanding gene regulatory mechanisms and translating these insights into functional targets. Here, we present a protocol for applying the network-enabled gene discovery pipeline (NEEDLE) to non-model plant species. We describe steps for environment setup, data preparation, computational analysis, expected outputs, and parameter considerations. NEEDLE integrates RNA sequencing (RNA-seq) processing, weighted gene co-expression analysis (WGCNA), Gene Network Inference with Ensemble of trees (GENIE3), and promoter conservation analysis to prioritize candidate transcriptional regulators.

Plant Sciences↗

An MBSE Framework to Identify Regulatory Gaps for Electrified Transport Aircraft

A typical aircraft certification process consists of obtaining a type, production, airworthiness, and continued airworthiness certificates. During this process, a type certification plan is created that includes the intended regulatory operating environment, the proposed certification basis, means of compliance, and a list of documentation to show compliance. Earlier work by the authors demonstrated a model-based framework for the management of these certification artifacts for normal category airplanes. Presently, it is expanded and adapted to consider certification for transport category airplanes regulated under 14 CFR Part 25, providing clear transparency and traceability between the text of the regulations and imposed requirements, contextual information, and specified test activities. In particular, a capability to identify potential gaps in the applicability of regulations for novel architectures such as electrified aircraft is proposed. This capability, based on mismatches between the functional intent and the corresponding prescribed physical implementation, is developed. A sample implementation of the proposed capability is presented for a notional electrified powertrain aircraft architecture.

electrified transport aircraft↗

Artificial Intelligence Transforming Post-Translational Modification Research

Post-Translational Modifications (PTMs) are covalent changes to amino acids that occur after protein synthesis, including covalent modifications on side chains and peptide backbones. Many PTMs profoundly impact cellular and molecular functions and structures, and their significance extends to evolutionary studies as well. In light of these implications, we have explored how artificial intelligence (AI) can be utilized in researching PTMs. Initially, rationales for adopting AI and its advantages in understanding the functions of PTMs are discussed. Then, various deep learning architectures and programs, including recent applications of language models, for predicting PTM sites on proteins and the regulatory functions of these PTMs are compared. Finally, our high-throughput PTM-data-generation pipeline, which formats data suitably for AI training and predictions is described. We hope this review illuminates areas where future AI models on PTMs can be improved, thereby contributing to the field of PTM bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗

A Guide for Public Utility Commissions: Building Internal Technical Capacity and Recruiting Talent for Grid Resilience

This guide offers insight into how PUCs can strategically expand their technical workforce to meet evolving gird resilience demands. It outlines critical skill sets needed to support informed regulatory decision-making around resilience, such as modeling and weather forecasting, electric power systems analysis, and advanced data interpretation. In addition, it provides strategies for developing technical talent both internally and through additional recruitment efforts. Two appendices provide a list of grid resilience training resources and a compendium of sample job descriptions that reflect grid resilience technical expertise for PUC consideration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

mathematical modeling↗

Simulation of Physics-Based 0-10Hz Strong Motion Using High Performance Computing Supporting Refinements to Regional Ground Motion Models for the Central Eastern US

In collaboration with the U.S. Nuclear Regulatory Commission (NRC) the LLNL has developed a computationally efficient simulation platform designed to perform physics-based ground motion simulations for crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using high-performance computing. The main objective of the earthquake simulations was to use synthetic ground motion to provide constrains to refinements of existing ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-10Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model (1994). In simulations performed during the first stage of this project the Saikia’s velocity model demonstrated better performance in modelling high frequency regional wave propagation for the CEUS region recorded during the Mw5.0 November 7, 2016, Cushing Oklahoma (Taylor et al., 2017), and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes. The proposed regional 3D model includes random perturbations to the 1D background model using the stochastic scheme of Pitarka and Mellors (2021). In addition, validation analysis of the rupture generator and regional wave propagation models, using comparisons with different GMMs for Mw6.5 and Mw7.0 scenario earthquakes in the CEUS region resulted in a very good match between the simulated and empirical ground motion models. For the purposes of seismic hazard assessment at the existing and planned nuclear power plants, NRC is interested in studies aimed at improving the current ground motion models (GMM) for both Stable Continental Regions (SCR) in the Central and Eastern US and Active Crustal Regions (ACR) in the Western US. Due to lack of recorded data, these improvements require synthetic data for short fault distances and large magnitude earthquakes for which the existing recorded data is not enough to uniquely constrain the GMMs. The need for simulations and strong motion data is especially critical for the CEUS region where we do not have recorded data from potentially large damaging earthquakes with moment magnitudes 6.0 and higher. In this the project, we focused on 10Hz simulations of Mw7.0 scenario earthquakes with strike slip and thrust faulting mechanisms. We used more than 50 Mw7.0 earthquake rupture scenarios to investigate the ground motion uncertainty due to unknown earthquake rupture parameters, in particular, the slip distribution, rupture velocity, and faulting mechanism, and their implication on ground motion amplification due to forward rupture directivity effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Regulatory Implications of Embedded Grid Energy Storage

Electricity is unique among commodities in that its supply chain was developed without a storage component. Every other resource commodity has the ability to store excess quantities built into its supply chain – in the form of granaries, warehouses, reservoirs, etc. This embedded storage creates a buffer for mismatches between supply and demand, stabilizing prices and protecting customers. Recent technological advances in cost-competitive energy storage technologies that are scalable and flexible have made the concept of embedded electrical storage feasible, but several regulatory questions remain. This paper summarizes energy regulatory structures in the U.S. and the implications that they would have for embedded storage on the electric grid. Regulatory challenges for embedded storage include the lack of underlying standards, inclusion in planning processes, ownership models, compensation, and metrics. Two possible pathways forward are explored: an incremental one including regulatory guidance regarding the evaluation of embedded storage in existing planning processes, and a complex one involving the revision of existing reliability standards or the development of a new standard specific to embedded storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis -regulatory elements

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling and Assessment of Integrated Hydroelectric Power and Hydrogen Energy Storage

Environmental and regulatory constraints are increasingly posing challenges to the optimal operation of hydroelectric facilities. Hydrogen energy storage (HES) is well-suited to address these challenges.Using excess or low-cost hydroelectric power during off-peak hours to produce hydrogen can help reduce water spills and unlock opportunities for energy arbitrage. Moreover, the oxygen byproduct of electrolysis can be used to improve the dissolved oxygen (DO) levels in tailrace water. %, a key water quality metric for hydroelectric facilities.This paper presents an innovative framework for modeling and assessing the integrated hydroelectric-hydrogen system, considering subsystem constraints and coupling, benefits in spill water reduction and DO mitigation, as well as diverse hydrogen utilization, including re-electrification, blending with natural gas, and direct sales. Comprehensive case studies were conducted to assess the techno-economic performance of the integrated system in different deployment scenarios.

Energy storage, Hydrogen, Hydropower, Optimization↗

Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability

The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Determinants affecting physical activity levels in animal models

Weight control is dependent on energy balance. Reduced energy expenditure (EE) associated with decreased physical activity is suggested to be a major underlying cause in the increasing prevalence of weight gain and obesity. Therefore, a better understanding of the biological determinants involved in the regulation of physical activity is essential. To facilitate interpretation in humans, it is helpful to consider the evidence from animal studies. This review focuses on animal studies examining the biological determinants influencing activity and potential implications to human. It appears that physical activity is influenced by a number of parameters. However, regardless of the parameter involved, body weight appears to play an underlying role in the regulation of activity. Furthermore, the regulation of activity associated with body weight appears to occur only after the animal achieves a critical weight. This suggests that activity levels are a consequence rather than a contributor to weight control. However, the existence of an inverse weight-activity relationship remains inconclusive. Confounding the results are the multifactorial nature of physical activity and the lack of appropriate measuring devices. Furthermore, many determinants of body weight are closely interlocked, making it difficult to determine whether a single, combination, or interaction of factors is important for the regulation of activity. For example, diet-induced obesity, aging, lesions to the ventral medial hypothalamus, and genetics all produce hypoactivity. Providing a better understanding of the biological determinants involved in the regulation of activity has important implications for the development of strategies for the prevention of weight gain leading to obesity and subsequent morbidity and mortality in the human population.

Review↗