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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Urban Air Mobility↗
NASA NTRSDate not supplied

Cyber Threats & Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗
NASA NTRS2022

Updraft Dynamics and Microphysics: On the Added Value of The Cumulus Thermal Reference Frame in Simulations of Aerosol–Deep Convection Interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether, or under which conditions, a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using the following two different reference frames: static cloudy updraft grid cells versus tracked cumulus thermals. In both frameworks, we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

aerosols↗
DOE OSTI2019

MCNP AND CFD MODELING OF A SODIUM FAST REACTOR SUB-ASSEMBLY CHANNEL TO CAPTURE LOCALIZED TEMPERATURE PEAKING

Typical evaluation tools for sodium-cooled fast reactors (SFR) use simplified neutronic/thermal models to efficiently compute the power and temperature distributions within the core. However, their modeling capability can be limited in extreme cases such as when sharp inter-assembly power gradients occur, or for non-standard SFR assembly geometries. Higher fidelity tools that rely on Monte Carlo methods for neutron transport, and Computational Fluid Dynamics (CFD) for thermal analysis, are better suited in these instances. The higher accuracy comes at the cost of higher computational expense. MCNP and STAR CCM+ were selected for this analysis. While MCNP is capable of generating pin-level power distributions for a whole-core SFR model, it is prohibitively expensive to then conduct CFD analysis for every single assembly. A semi-empirical model was therefore developed to rapidly estimate pin temperature distributions throughout the whole core. It relies on a geometric correction factor for turbulent flow-mixing. The correction factor is obtained from a CFD simulation of a single fuel assembly with a uniform power distribution and an adiabatic boundary condition. Without using CFD, each sub-channel outlet temperature is calculated separately using 1-D heat-balance and Nusselt number correlations and the MCNP calculated pin-powers. The rudimentary 1-D model is then corrected for the flow-mixing effect based on the CFD data. The temperature calculation is performed by a code written in the Python language called CFD Monte-Carlo Developed Reconstruction of Sub-channel at a Quasi-Representative Level (CMDR-SQRL). CMDR-SQRL was shown to adequately predict CFD evaluated temperature distribution for a wide range of SFR configurations, including an extreme case with fuel assemblies nearby containing moderating material. The agreement demonstrates how geometric and power-driven effects can be decoupled within an SFR assembly. CMDR-SQRL is intended to be mainly used for scoping studies to provide core-wide evaluations efficiently.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Vitrification of High-Level Waste: how to Select the Best Suited Technology - 18117

Since more than 30 years now, a number of countries have selected and operated vitrification as the best industrial practice for safely and durably immobilizing the most active liquid waste. This now significant worldwide experience covers a wide range of waste compositions, from concentrated alkaline defense waste sludges with a variety of salts and chemicals (Na, Fe, Al, Cr, sulphate,... ) to relatively clear acidic HLLW from commercial, low salt, PUREX-type processes, waste that include dissolved cladding material (Al, Mg, stainless steel), waste that include high levels of noble metals and fines... The activity levels vary from 40- year old defense waste to relatively young waste from high burn-up commercial fuel. The current throughputs vary from about 5 kg/h of glass to about 90 kg/h of glass per melter. Even higher throughputs are currently being considered for Hanford facility for instance. In order to cope with the range of waste compositions, glass compositions have also evolved from low melting temperature borosilicate or phosphate glass to glass or glass ceramics with higher melting temperatures. More complex matrices are currently under study in a number of countries, to immobilize more complex waste and / or increase waste loadings. Each challenge is unique and, for each challenge, it is necessary to select the best combination of waste form and technology. For instance for very active solutions with high levels of noble metal particles that could settle, increase apparent glass viscosity, and impact electrical conductivity, one would select borosilicate glass in the mechanically-stirred hot wall induction melter with bottom pouring that has proven its efficiency in industrial conditions at La Hague. For high glass throughputs with low solids in a borosilicate melt (typically Defense waste), ceramic melters have proven their reliability and efficiency. For matrices that need higher temperatures, or with very high corrosiveness, Cold-Crucible Induction Melters are now considered, with one first industrial implementation at La Hague to produce borosilicate glass and a glass-ceramic. All these technologies have been improved over the years to increase throughput, waste loading, melting temperature, reliability... Other types of waste are now being studied worldwide, and for each, it is necessary to carefully select the adapted waste form and technology. The technologies studied will range from traditional technologies (such as hot-wall induction melter technology and liquid-fed ceramic melter technologies) to the more recent advanced technologies (such as Cold Crucible Induction Melter or Advanced Ceramic melters). In addition, the field of vitrification is extending to other types of waste; the current advances in this field will also be described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2014

The Influence of Free Space Environment in the Mission Life Cycle: Material Selection

The natural space environment has a great influence on the ability of space systems to perform according to mission design specification. Understanding the natural space environment and its influence on space system performance is critical to the concept formulation, design, development, and operation of space systems. Compatibility with the natural space environment is a primary factor in determining the functional lifetime of the space system. Space systems being designed and developed today are growing in complexity. In many instances, the increased complexity also increases its sensitivity to space environmental effects. Sensitivities to the natural space environment can be tempered through appropriate design measures, material selection, ground processing, mitigation strategies, and/or the acceptance of known risks. The design engineer must understand the effects of the natural space environment on the space system and its components. This paper will discuss the influence of the natural space environment in the mission life cycle with a specific focus on the role of material selection.

Edwards, David L.↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
DOE OSTI2025

DNABERT-S: pioneering species differentiation with species-aware DNA embeddings

SUMMARY: We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e. DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 28 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. AVAILABILITY AND IMPLEMENTATION: Model, codes, and data are publically available at https://github.com/MAGICS-LAB/DNABERT_S.

Zhou, Zhihan↗
DOE OSTI2021

Microbial Biomass in Soils Receiving Varying Levels of Organic Inputs - A Data Compilation

This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Updraft Dynamics and Microphysics: On the Added Value of the Cumulus Thermal Reference Frame in Simulations of Aerosol–Deep Convection Interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether or under what conditions a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using two different reference frames: static cloudy-updraft grid cells versus tracked cumulus thermals. In both frameworks we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy-updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy-updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy-updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

Daniel Hernandez-Deckers↗
DOE OSTI2019

Integrating Interactive Jupyter Notebooks at the BNL SDCC

At the SDCC we are deploying a Jupyterhub infrastructure to enable scientists from multiple disciplines to access our diverse compute and storage resources. One major design goal was to avoid rolling out yet another compute backend, but rather to leverage our pre-existing resources via our batch systems (HTCondor and Slurm). Challenges faced include creating a frontend that allows users to choose what HPC resources they have access to as well as selecting containers or environments, delegating authentication to a MFA-enabled proxy, and automating deployment of multiple hub instances. This paper covers the design and features of our Jupyterhub service.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Carbon fiber synthesis from pitch: Insights from ReaxFF based molecular dynamics simulations

Despite the potential to lowering fabrication costs of pitch-based carbon fiber (CF) compared to polyacrylonitrile-based CF, large scale utilization is currently limited by the complexity in manufacturing. This is mainly due to the lack of consistency between the pitch structure/chemistry and CF properties under different processing conditions. Here, we employed full atomistic simulations based on reactive force fields to investigate the conversion of pitch precursors to CFs. Additionally, it was found that at the carbonization stage, the consumption rates of precursors, gas formations, and solid yields (carbonized CFs) are all dependent on the composition and arrangement of molecular moieties in the precursor. Specifically, precursors with sp 3 carbons in the cata-condensed core area have limited decomposition pathways (i.e., limited reaction sites), which leads to the formation of carbonized CFs with similar compositions. Furthermore, carbonized CFs possess distinct structural characteristics, and finally lead to the formation of CFs with different moduli. By analyzing CF crystallinity and elemental composition, general rationales are proposed for the selection of optimal precursors and processing conditions, and thus shed lights on parameter screening during industrial CF synthesis. For instance, inclusion of sp 3 carbons in cata- condensed rings can be preferred over the presence of sp 3 carbons on side chains.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1980

An approach for management of geometry data

The strategies for managing Integrated Programs for Aerospace Design (IPAD) computer-based geometry are described. The computer model of geometry is the basis for communication, manipulation, and analysis of shape information. IPAD's data base system makes this information available to all authorized departments in a company. A discussion of the data structures and algorithms required to support geometry in IPIP (IPAD's data base management system) is presented. Through the use of IPIP's data definition language, the structure of the geometry components is defined. The data manipulation language is the vehicle by which a user defines an instance of the geometry. The manipulation language also allows a user to edit, query, and manage the geometry. The selection of canonical forms is a very important part of the IPAD geometry. IPAD has a canonical form for each entity and provides transformations to alternate forms; in particular, IPAD will provide a transformation to the ANSI standard. The DBMS schemas required to support IPAD geometry are explained.

Dube, R. P.↗
DOE OSTI2018

Annotation of the Corymbia terpene synthase gene family shows broad conservation but dynamic evolution of physical clusters relative to Eucalyptus

Terpenes are economically and ecologically important phytochemicals. Their synthesis is controlled by the terpene synthase (TPS) gene family, which is highly diversified throughout the plant kingdom. The plant family Myrtaceae are characterised by especially high terpene concentrations, and considerable variation in terpene profiles. Many Myrtaceae are grown commercially for terpene products including the eucalypts Corymbia and Eucalyptus. Eucalyptus grandis has the largest TPS gene family of plants currently sequenced, which is largely conserved in the closely related E. globulus. However, the TPS gene family has been well studied only in these two eucalypt species. The recent assembly of two Corymbia citriodora subsp. variegata genomes presents an opportunity to examine the conservation of this important gene family across more divergent eucalypt lineages. Manual annotation of the TPS gene family in C. citriodora subsp. variegata revealed a similar overall number, and relative subfamily representation, to that previously reported in E. grandis and E. globulus. Many of the TPS genes were in physical clusters that varied considerably between Eucalyptus and Corymbia, with several instances of translocation, expansion/contraction and loss. Notably, there was greater conservation in the subfamilies involved in primary metabolism than those involved in secondary metabolism, likely reflecting different selective constraints. The variation in cluster size within subfamilies and the broad conservation between the eucalypts in the face of this variation are discussed, highlighting the potential contribution of selection, concerted evolution and stochastic processes. Finally, these findings provide the foundation to better understand terpene evolution within the ecologically and economically important Myrtaceae.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

The brightness of Jupiter's satellite Io following emergence from eclipse - Selected observations, 1981-1989

Io's brightness was monitored following emergence from eclipse by Jupiter on 14 occasions during the Jupiter apparitions from 1981 to 1989 and no instance is found of what has been called posteclipse brightening. If all the observations are averaged, a 2 percent effect cannot be ruled out; however, this effect is also the size of the rms errors of the summed data set. If condensation followed by sublimation of SO2 frost is hypothesized to be the mechanism which causes posteclipse brightening, then solar insolation alone may not be sufficient to remove an optically thick layer of SO2 frost in the time required to conform with the positive reports of posteclipse brightening in the literature. An additional source of energy is required, such as warming caused by the impact of magnetospheric particles as they dissipate the energy of their motion into Io's surface.

Nelson, Robert M.↗
DOE OSTI2019

New Tabu Algorithm for Positioning Mining Drillholes with Blocks Uncertainty

This paper proposes a new approach to the mining exploration drillholes positioning problem (DPP) that incorporates both geostatistical and optimization techniques. A metaheuristic was developed to solve the DPP taking into account an uncertainty index that quantifies the reliability of the current interpretation of the mineral deposit. The uncertainty index was calculated from multiple deposit realizations obtained by truncated Gaussian simulations conditional to the available drillholes samplings. A linear programming model was defined to select the subset of future drillholes that maximizes coverage of the uncertainty. A Tabu Search algorithm was developed to solve large instances of this set partitioning problem. The proposed Tabu Search algorithm is shown to provide good quality solutions approaching 95% of the optimal solution in a reasonable computing time, allowing close to optimal coverage of uncertainty for a fixed investment in drilling.

58 GEOSCIENCES↗
DOE OSTI2019

Transmission Constraint Filtering in Large-Scale Security-Constrained Unit Commitment

When solving the security-constrained unit commitment problem, one of the most complicating factors is handling the large number of transmission constraints, corresponding to both base case and N - 1 line contingency scenarios. Although it is well known that only a few of these constraints need to be enforced, identifying this critical subset of constraints efficiently remains a challenge. In this letter, we propose a novel and simple iterative contingency-screening procedure that is able to eliminate 99.4% of the constraints selected by existing iterative methods, allowing for the solution of much larger-scale problems. We report computational results in realistic instances with up to 6468 buses and 9000 transmission lines. Furthermore, the method was also independently implemented and evaluated at MISO, where it performed faster than alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Failure Formulations in Modular Plasticity Models

Computational prediction of ductile failure remains a challenging and important problem as demonstrated by the recent Sandia Fracture Challenges. In addition to emphasizing the complexity of such problems, the variety of solution strategies also highlighted the number of possible approaches to this problem. A common engineering approach for such efforts is to use a failure model in conjunction with element deletion. In the second Sandia Fracture Challenge, for instance, nine of the fourteen teams used some form of element deletion. For such schemes, a critical decision pertains to the selection of the appropriate failure model; of which many may be found in the literature (see the review of Corona and Reedlunn). The variety may also be observed in the aforementioned second Sandia Fracture Challenge in which at least eight different failure criteria are listed for the nine element deletion based approaches. The selection of the appropriate failure model is a difficult challenge depending on the material being considered and such criteria can variously depend on stress state (i.e. triaxiality, Lode angle) and loading conditions (i.e. strain rate, temperature). Separate implementations of each criteria with different plasticity models can be a repetitive and cumbersome process which may limit available models for an engineering analyst. To mitigate this issue, an effort was pursued to flexibly implement failure models in which different failure models could be specified and utilized within the same elastic-plastic constitutive routine by simply changing the input syntax. Similarly, the same models are implemented across a suite of elastic-plastic formulations enabling consistent definitions. As will be discussed later, a specific "modular failure" model is also implemented which allows for the selection or specification of different dependencies depending on the current need. At this stage, this effort is limited to defining failure models; progression/damage evolution in the constitutive model is not treated and left to future efforts.

42 ENGINEERING↗