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At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Full wave modeling of radio-frequency beams in tokamaks in the electron cyclotron frequency range

Simulation of full wave, without paraxial approximation, high-resolution solution of wave equations in frequency domain in the electron cyclotron resonance (ECR) frequency range for realistic Tokamak plasma parameters became possible by using recently formulated hybrid iterative algorithm [Svidzinski et al., Phys. Plasmas 25, 082509 (2018)] for numerically solving discretized wave equations. This approach combines time evolution and iterative relaxation techniques into iteration cycles. This algorithm is implemented in 2D code FullWave, solving wave equations in Tokamaks in cold and hot plasma models, and it has been tested in 3D full wave iterative RF beams simulation tool, which is presently being developed to model 3D ECRH RF beams in fusion devices using dynamic grid adaptation. The results of 2D full wave modeling, assuming specified toroidal mode number, of ECRH RF beams in DIII-D plasma, performed in the cold and hot plasma models for outboard and top launch scenarios using FullWave are presented. Nonlocal hot plasma response model, based on accurate numerical solution of linearized Vlasov equation, is used to model beam propagation and absorption in the 2nd electron cyclotron harmonic region. Demonstration of capability of the hybrid iterative algorithm to model ECRH RF beams in 3D is made by simulating a substantial part of realistic beam in DIII-D, launched from outboard side of the machine. All relevant physics of RF beam propagation, most of which is not captured in paraxial approximation, such as beam's divergence, interference between the X and O modes in the beam, X-O mode conversion, beam splitting into the X and O mode beams, transformation of beam's cross section, and absorption at the 2nd electron cyclotron harmonic, is captured in the simulations. A numerical technique to find an optimal beam polarization at the launcher to launch a nearly pure X or O mode beam in plasma is developed and tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π-π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single–amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single– and multiple–amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Harrivel, Angela↗

DOE OSTI2024

Structure-guided discovery of ancestral CRISPR-Cas13 ribonucleases

The RNA-guided ribonuclease CRISPR-Cas13 enables adaptive immunity in bacteria and programmable RNA manipulation in heterologous systems. Cas13s share limited sequence similarity, hindering discovery of related or ancestral systems. Here, to address this, we developed an automated structural-search pipeline to identify an ancestral clade of Cas13 (Cas13an) and further trace Cas13 origins to defense-associated ribonucleases. Despite being one-third the size of other Cas13s, Cas13an mediates robust programmable RNA depletion and defense against diverse bacteriophages. However, unlike its larger counterparts, Cas13an uses a single active site for both CRISPR RNA processing and RNA-guided cleavage, revealing that the ancestral nuclease domain has two modes of activity. Discovery of Cas13an deepens our understanding of CRISPR-Cas evolution and expands opportunities for precision RNA editing, showcasing the promise of structure-guided genome mining.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1997

On Efficient Parallel Implementation of Moving Body Overset Grid Methods

An investigation into the parallel performance of moving-body overset grid methods will be presented. Parallel versions of the OVERFLOW flow solver, DCF3D domain connectivity software, and SIXDO six-degree-of-freedom routine are coupled with an automatic load balance routine and tested for 3D Navier-Stokes calculations on the IBM SP2. The primary source of parallel inefficiency in moving and problems are the domain connectivity costs with DCF 3D. Although this algorithm constitutes a relatively low fraction of the total solution cost (e.g. 10-20%) in calculations on serial machines, the consequently cause a significant degradation in the overall parallel performance. The paper will highlight some approaches for improving the scalability of DCF3D. The paper will present results of a proposed new load balancing scheme that seeks more equal distribution of the inter-grid boundary points in order to more evenly load balance the donor search costs associated with DCF3D. Some preliminary results will also be given from a new solution-adaption algorithm coupled with OVERFLOW which incorporates overset cartesian grids with various levels of refinement. The measured parallel performance from a descending delta-wing configuration and a generic store-separation from a wing/pylon case will be presented.

Wissink, Andrew M.↗

DOE OSTI2023

Smart Mobility in the Cloud: Enabling Real-Time Situational Awareness and Cyber-Physical Control Through a Digital Twin for Traffic

This article presents the design, implementation, and use cases of the Chattanooga Digital Twin (CTwin) towards the vision for next-generation smart city applications for urban mobility management. CTwin is an end-to-end web-based platform that incorporates various aspects of the decision-making process for optimizing urban transportation systems in Chattanooga, Tennessee, to reduce traffic congestion, incidents, and vehicle fuel consumption. The platform serves as a cyberinfrastructure to collect and integrate multi-domain urban mobility data from various online repositories and Internet of Things (IoT) sensors, covering multiple urban aspects (e.g., traffic, natural hazards, weather, and safety) that are relevant to urban mobility management. The platform enables advanced capabilities for: (a) real-time situational awareness on traffic and infrastructure conditions on highways and urban roads, (b) cyber-physical control for optimizing traffic signal timing, and (c) interactive visual analytics on big urban mobility data and various metrics for traffic prediction and transportation performance evaluation. The platform is designed using a multi-level componentization paradigm and is implemented using modular and adaptive architecture, rendering it as a generalizable and extendable prototype for other urban management applications. We present several use cases to demonstrate CTwin's core capabilities for supporting decision-making in smart urban mobility management.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Applying Time-Parallelization to Turbulent Flows

Parallelization of the temporal domain is explored for the solution of turbulent flows. Multigrid reduction-in-time (MGRIT) is used to advance the large-scale fluid dynamics in time sequentially on the coarsest space-time grid but propagate the information in time parallel on all other levels. The goal of this process is to accurately and efficiently resolve the coarse-scale turbulence structure and use that to drive the fine-scales of the turbulent flow. The extra forcing from nonlinear multigrid facilitates the coupling and interaction between fine and coarse scales, through which the multiscale nonlinear physics is properly captured. Adaptive mesh refinement is employed to finely resolve only the regions with strong gradients, which provides further computational efficiency. The underlying computational fluid dynamics solver is a fourth-order finite-volume scheme with the standard 4-stage Runge-Kutta method. An advanced approach is devised and implemented to enable MGRIT to solve highly turbulent flows successfully. Furthermore, the method is applied to solve a Taylor-Green vortex problem and a doubleshear-layer turbulent mixing flow. Results are promising, validating that MGRIT with the filtering approach has the potential to efficiently solve general turbulent flows.

Computational Fluid Dynamics↗

DOE OSTI2021

In Situ High-Pressure Synthesis of New Outstanding Light-Element Materials under Industrial P-T Range

High-pressure synthesis (which refers to pressure synthesis in the range of 1 to several GPa) adds a promising additional dimension for exploration of compounds that are inaccessible to traditional chemical methods and can lead to new industrially outstanding materials. It is nowadays a vast exciting field of industrial and academic research opening up new frontiers. In this context, an emerging and important methodology for the rapid exploration of composition-pressure-temperature-time space is the in situ method by synchrotron X-ray diffraction. This review introduces the latest advances of high-pressure devices that are adapted to X-ray diffraction in synchrotrons. It focuses particularly on the “large volume” presses (able to compress the volume above several mm3 to pressure higher than several GPa) designed for in situ exploration and that are suitable for discovering and scaling the stable or metastable compounds under “traditional” industrial pressure range (3–8 GPa). We illustrated the power of such methodology by (i) two classical examples of “reference” superhard high-pressure materials, diamond and cubic boron nitride c-BN; and (ii) recent successful in situ high-pressure syntheses of light-element compounds that allowed expanding the domain of possible application high-pressure materials toward solar optoelectronic and infra-red photonics. Finally, in the last section, we summarize some perspectives regarding the current challenges and future directions in which the field of in situ high-pressure synthesis in industrial pressure scale may have great breakthroughs in the next years.

36 MATERIALS SCIENCE↗

NASA NTRS1991

The computation of three-dimensional flows using unstructured grids

A general method is described for automatically discretizing, into unstructured assemblies of tetrahedra, the three-dimensional solution domains of complex shape which are of interest in practical computational aerodynamics. An algorithm for the solution of the compressible Euler equations which can be implemented on such general unstructured tetrahedral grids is described. This is an explicit cell-vertex scheme which follows a general Taylor-Galerkin philosophy. The approach is employed to compute a transonic inviscid flow over a standard wing and the results are shown to compare favorably with experimental observations. As a more practical demonstration, the method is then applied to the analysis of inviscid flow over a complete modern fighter configuration. The effect of using mesh adaptivity is illustrated when the method is applied to the solution of high speed flow in an engine inlet.

Morgan, K.↗

DOE OSTI2025

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

MarK, a Novosphingobium aromaticivorans kinase required for catabolism of multiple aromatic monomers

The aromatic compounds used in a variety of industrial products are currently obtained from nonrenewable petroleum sources. Alternatively, the plant polymer lignin is an abundant renewable source of aromatics, and its depolymerization generates a variety of products that can include acetovanillone, a vanillin derivative containing an acetyl side chain. The Alphaproteobacterium Novosphingobium aromaticivorans DSM12444 can metabolize several chemically modified aromatics in deconstructed lignin, but not acetovanillone. In this work, adaptive laboratory evolution identified a single amino acid change in the previously uncharacterized gene product Saro_1862 that is necessary and sufficient for N. aromaticivorans growth with acetovanillone as a sole growth substrate, as well as other aromatic monomers not metabolized by wild-type cells. We show that a glutamate (E) to lysine (K) substitution at amino acid residue 16 of Saro_1862 results in a ~1600-fold increase in the rate of ATP-dependent acetovanillone phosphorylation. We also find that recombinant Saro_1862 E16K phosphorylates several other aromatic compounds in vitro , defining the first reported catalytic activity for the widespread UPF0261 protein domain contained in Saro_1862. Thus, we propose naming Saro_1862 MarK, for multiple aromatic kinase. A 1.57 Å crystal structure of MarK E16K predicts that the E16K substitution lies in a potential ATP binding site, suggesting how this amino acid change increased catalytic activity. A search for homologs of MarK and other proteins required for acetovanillone degradation predicts that this pathway for aromatic metabolism exists throughout the bacterial phylogeny.

Novosphingobium↗

DOE OSTI2021

Isoform-specific functions of synaptopodin-2 variants in cytoskeleton stabilization and autophagy regulation in muscle under mechanical stress

Highlights: • Muscle cells express different synaptopodin-2 isoforms with individual functions. • Reduced SYNPO2 expression results in enhanced vulnerability of myofibrils. • SYNPO2e recruites BAG3 to mechanically stressed myofibrillar areas. • SYNPO2 is an organizer and regulator of BAG3-containing proteostasis systems. • BAG3 forms functionally distinct protein complexes with different SYNPO2 isoforms. Protein homeostasis (proteostasis) in multicellular organisms depends on the maintenance of force-bearing and force-generating cellular structures. Within myofibrillar Z-discs of striated muscle, isoforms of synaptopodin-2 (SYNPO2/myopodin) act as adapter proteins that are engaged in proteostasis of the actin-crosslinking protein filamin C (FLNc) under mechanical stress. SYNPO2 directly binds F-actin, FLNc and α-actinin and thus contributes to the architectural features of the actin cytoskeleton. By its association with autophagy mediating proteins, i.e. BAG3 and VPS18, SYNPO2 is also engaged in protein quality control and helps to target mechanical unfolded and damaged FLNc for degradation. Here we show that deficiency of all SYNPO2-isoforms in myotubes leads to decreased myofibrillar stability and deregulated autophagy under mechanical stress. In addition, isoform-specific proteostasis functions were revealed. The PDZ-domain containing variant SYNPO2b and the shorter, PDZ-less isoform SYNPO2e both localize to Z-discs. Yet, SYNPO2e is less stably associated with the Z-disc than SYNPO2b, and is dynamically transferred into FLNc-containing myofibrillar lesions under mechanical stress. SYNPO2e also recruits BAG3 into these lesions via interaction with the WW domain of BAG3. Our data provide evidence for a role of myofibrillar lesions as a transient quality control compartment essential to prevent and repair contraction-induced myofibril damage in muscle and indicate an important coordinating activity for SYNPO2 therein.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Evaluating Resilience of Water Distribution Networks to Operational Failures from Cyber-Physical Attacks

Water cyber-physical systems (CPSs) have gained increasing interest to improve operational efficiency and reliability. However, due to growing exposure to cyber-physical attacks, cybersecurity and resilience against the attacks have become significant concerns. There have been efforts to improve cybersecurity in water CPSs, yet few attempts to investigate resilience against cyber-physical attacks. This study contributes to characterizing resilience of a water CPS and investigating potential resilience strategies. An advanced resilience measure integrating withstanding, absorptive, adaptive, and restorative capability of a system is proposed and applied to the C-town water distribution network (WDN) for 15 failure set scenarios with a pressure-driven hydraulic simulation. The results provide identification of failure sets and unfavorable operational conditions that make the system more vulnerable to the cyber-physical attacks and in turn produce low resilience and capabilities. It is also found that, after recovery of a disrupted component, adjustment of overall operational interactions across system components is needed for complete restoration of disrupted functionality. The findings provide insights on infrastructure investment with resilience strategies in cyber and physical water system domains.

Shin, Sangmin↗

DOE OSTI2022

Resilient Adaptive Parallel sImulator for griD (RAPID): An Open Source Power System Simulation Toolbox

Not Available

42 ENGINEERING↗

DOE OSTI2022

A Study on Efficient Reinforcement Learning Through Knowledge Transfer

Although Reinforcement Learning (RL) algorithms have made impressive progress in learning complex tasks over the past years, there are still prevailing short-comings and challenges. Specifically, the sample-inefficiency and limited adaptation across tasks often make classic RL techniques impractical for real-world applications despite the gained representational power when combining deep neural networks with RL, known as Deep Reinforcement Learning (DRL). Recently, a number of approaches to address those issues have emerged. Many of those solutions are based on smart DRL architectures that enhance single task algorithms with the capability to share knowledge between agents and across tasks by introducing Transfer Learning (TL) capabilities. Here this survey addresses strategies of knowledge transfer from simple parameter sharing to privacy preserving federated learning and aims at providing a general overview of the field of TL in the DRL domain, establishes a classification framework, and briefly describes representative works in the area.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Analytic model for neutral penetration and plasma fueling

Neutral atoms recycled from wall interaction interact with confined plasma, thereby refuelling it, most strongly in the region closest to the wall. This occurs near the X-point in diverted configurations, or else near the wall itself in limited configurations. A progression of analytic models is developed for neutral density in the vicinity of a planar or linear source in an ionising domain. First-principles neutral transport simulations with DEGAS2 are used throughout to test the validity and limits of the model when using equivalent sources. The model is further generalised for strong plasma gradients or the inclusion of charge exchange. An important part of the problem of neutral fuelling from recycling is thereby isolated and solved with a closed-form analytic model. A key finding is that charge exchange with the confined plasma can be significantly simplified with a reasonable sacrifice of accuracy by treating it as a loss. The several assumptions inherent to the model (and the simulations with which it is compared) can be adapted according to the particular behaviour of neutrals in the divertor and the manner in which they cross the separatrix.

fusion plasma↗

DOE OSTI2026

Cis-regulatory evolution shapes facial diversity in birds and mammals

Birds and mammals exhibit extraordinary facial diversity, reflecting adaptations to distinct ecological niches and feeding strategies. While core face-building developmental programs are conserved and orchestrated by interactions between ectodermal organizers and the underlying mesenchyme, mechanisms driving facial shape variation remain poorly understood. Here, we integrate single-cell transcriptomic and chromatin accessibility profiling of mouse and chicken developing face to construct a comparative regulatory map. Although both ectodermal and mesenchymal populations display distinct regulatory features in each species, the mesenchyme exhibits markedly greater divergence, pointing to its central role in shaping facial morphology. We further reveal unexpected molecular complexity in the main face-shaping organizer, including a mouse-specific Shh/Wnt5a expression domain. At key morphogen loci (Bmp4, Fgf8, and Wnt5a), conserved and lineage-specific enhancers exhibit spatially restricted activity patterns that mirror divergent signaling domains. These findings demonstrate how cis-regulatory evolution modulates conserved developmental programs to generate morphological novelty, providing a valuable resource for studying vertebrate facial evolution.

Kyomen, Stella [Max Planck Institute for Evolution↗