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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The CCR4‐NOT complex component NOT1 regulates RNA‐directed DNA methylation and transcriptional silencing by facilitating Pol IV‐dependent siRNA production

Summary Small interfering RNAs (siRNAs) are responsible for establishing and maintaining DNA methylation through the RNA‐directed DNA methylation (RdDM) pathway in plants. Although siRNA biogenesis is well known, it is relatively unclear about how the process is regulated. By a forward genetic screen in Arabidopsis thaliana , we identified a mutant defective in NOT1 and demonstrated that NOT1 is required for transcriptional silencing at RdDM target genomic loci. We demonstrated that NOT1 is required for Pol IV‐dependent siRNA accumulation and DNA methylation at a subset of RdDM target genomic loci. Furthermore, we revealed that NOT1 is a constituent of a multi‐subunit CCR4‐NOT deadenylase complex by immunoprecipitation combined with mass spectrometry and demonstrated that the CCR4‐NOT components can function as a whole to mediate chromatin silencing. Therefore, our work establishes that the CCR4‐NOT complex regulates the biogenesis of Pol IV‐dependent siRNAs, and hence facilitates DNA methylation and transcriptional silencing in Arabidopsis.

Zhou, Hao‐Ran↗
DOE OSTI2022

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications. In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume. Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

42 ENGINEERING↗
DOE OSTI2025

FreeMHD: Validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows

The extreme heat fluxes in the divertor region of tokamaks may require an alternative to solid plasma-facing components, for the extraction of heat and the protection of the surrounding walls. Flowing liquid metals are proposed as an alternative, but raise additional challenges that require investigation and numerical simulations. Free surface designs are desirable for plasma-facing components, but steady flow profiles and surface stability must be ensured to limit undesirable interactions with the plasma. Previous studies have mainly used steady-state, 2D, or simplified models for internal flows and have not been able to adequately model free-surface liquid metal (LM) experiments. Therefore, FreeMHD has been recently developed as an open-source magnetohydrodynamics (MHD) solver for free-surface electrically conductive flows subject to a strong external magnetic field. The FreeMHD solver computes incompressible free-surface flows with multi-region coupling for the investigation of MHD phenomena involving fluid and solid domains. The model utilizes the finite-volume OpenFOAM framework under the low magnetic Reynolds number approximation. FreeMHD is validated using analytical solutions for the velocity profiles of closed channel flows with various Hartmann numbers and wall conductance ratios. Next, experimental measurements are then used to verify FreeMHD, through a series of cases involving dam breaking, 3D magnetic fields, and free-surface LM flows. These results demonstrate that FreeMHD is a reliable tool for the design of LM systems under free surface conditions at the reactor scale. Furthermore, it is flexible, computationally inexpensive, and can be used to solve fully 3D transient MHD flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Integrating Intelligent Hydro-informatics into an effective Early Warning System for risk-informed urban flood management

The urban drainage system constantly facing flooding issues in coastal and urban areas. Robust and accurate urban flood management, particularly considering fast-moving compound floods, is crucial to minimize the impact of flood disasters in coastal cities. Till now, Ho Chi Minh City (HCMC) lacks an effective means of urban flood management because of flood risk communication among residents. Existing flood risk communication tools rely on post-disaster flood model outcomes and data. Therefore, this research proposes a real-time Early Urban Flooding Warning System (EUFWS) integrated with a user-friendly web and app interface. The backbone of this system consists of flood models developed using machine learning (ML) algorithms, combined with big data and Web-GIS visualization, with ML serving as the core for constructing the EUFWS. EUFWS offer several key advantages: they are available at all times, accessible from anywhere, and provide a real-time, multi-user working platform. Additionally, the system is flexible, allowing for the easy addition of components and services and scalable, adjusting to workload demands. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. EUFWS have been successfully deployed in Thu Duc City, Vietnam, as a case study and are operating effectively. Research results indicate that EUFWS supported decision-makers to be effectively risk informed and make intelligent decisions during urban flood emergencies. Finally, this underscores the significant potential of integrating ML and information technology to enhance the management of smart urban drainage systems in flood-prone cities worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Alicyclic carboxylic acids in soil humic acid as detected with ultrahigh resolution mass spectrometry and multi-dimensional NMR

It has been well accepted that humic acids in soils comprise both aromatic and aliphatic structural units that harbor mainly oxygenated functional groups such as carboxylic acids, aldehydes, ketones, and hydroxyl groups. Recent mass spectral data obtained from electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICRMS) suggest that the main functional groups in humic acids are carboxylic acids bound to both alicyclic and condensed aromatic molecules. It was suggested that these structural entities originate from oxidation of lignin. To provide additional support, detailed structural characteristics were obtained here using several multi-dimensional nuclear magnetic resonance (NMR) techniques to observe the molecular connectivity of humic acid components, with a focus on carboxylic acids in particular. The humic acid sample examined had been shown to exhibit structural characteristics similar to a larger set of soil humic acids. Here in this study, many carboxylic acid resonances were found to correlate with protons that could be assigned to aliphatic and alicyclic chemical shift regions. Functional groups with heteroatoms such as alcohols, some olefins and an assortment of methyl groups were found to correlate within 2–3 bonds of carboxylic acid groups. The collection of structural components and their proximity to a variety of carboxylic groups supports the occurrence of carboxylated alicyclic molecules as important elements of the aliphatic portion of soil humic acids and a pathway from lignin is consistent with recent findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Latest Minimum Bias and Underlying Event measurements with the ATLAS Detector

The modelling of Minimum Bias and Underlying Event is a crucial component in the description of soft Quantum Chromodynamics processes. They are both described by multi-parton interaction models, the result of proton collisions containing more than one partonic interaction due to collective and beam remnant effects. Recent studies by the ATLAS Experiment at the LHC aiming at measuring Charged-Particle distributions and the properties of the Underlying Event are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Predicting opioid receptor binding affinity of pharmacologically unclassified designer substances using molecular docking

Opioids represent a highly-abused and highly potent class of drugs that have become a significant threat to public safety. Often there are little to no pharmacological and toxicological data available for new, illicitly used and abused opioids, and this has resulted in a growing number of serious adverse events, including death. The large influx of new synthetic opioids permeating the street-drug market, including fentanyl and fentanyl analogs, has generated the need for a fast and effective method to evaluate the risk a substance poses to public safety. In response, the US FDA’s Center for Drug Evaluation and Research (CDER) has developed a rapidly-deployable, multi-pronged computational approach to assess a drug’s risk to public health. A key component of this approach is a molecular docking model to predict the binding affinity of biologically uncharacterized fentanyl analogs to the mu opioid receptor. The model was validated by correlating the docking scores of structurally diverse opioids with experimentally determined binding affinities. Fentanyl derivatives with subnanomolar binding affinity at the mu receptor (e.g. carfentanil and lofentanil) have significantly lower binding scores, while less potent fentanyl derivatives have increased binding scores. The strong correlation between the binding scores and the experimental binding affinities suggests that this approach can be used to accurately predict the binding strength of newly identified fentanyl analogs at the mu receptor in the absence of in vitro data and may assist in the temporary scheduling of those substances that pose a risk to public safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

New Insertion Device Control System for the APS Upgrade

New Hybrid Permanent Magnet Undulators (HPMUs) have been designed and manufactured using servo motors for precise and reliable gap motion control for the Advanced Photon Source Upgrade (APS-U) project. Meanwhile, existing HPMUs equipped with legacy stepper motors are systematically replaced with servo motors. In parallel with mechanical modifications of the undulators, a comprehensive upgrade has been implemented for the control of the devices. This upgrade includes integration of standardized industrial components for replacement of motor controllers and motor drives using the Kollmorgen Programmable Controller Multi-axis Master (PCMM) controllers and the AKD2G series servo drives. Soft Input Output Controllers (IOCs) are developed and deployed to replace the legacy VME-based IOCs for both single-period undulators and Revolver undulators. In this paper, we will present the architecture of the new insertion device control system, including control mechanisms, interlock protocols, and tools for diagnostics and troubleshooting.

Li, W.↗
DOE OSTI2024

Elucidating and contrasting the mechanisms for Mg and Ca sulfate ion-pair formation with multi-level embedded quantum mechanics/molecular dynamics simulations

Here, solutions and minerals containing sulfate (SO 4 2- ), and Ca 2+ and Mg 2+ cations, are ubiquitous throughout the lithosphere and are significant components of seawater, thus presenting a prototypical system for the study of strong electrolytes and crystal nucleation mechanisms. However, despite their relative abundance, key questions remain unanswered about the most fundamental atomic-level steps of their mineralization pathways and aqueous dynamics. Here, we carry out enhanced sampling multi-level molecular dynamics (MD) embedded correlated wavefunction theory simulations to elucidate ion-pairing mechanisms for Mg–SO 4 and Ca–SO 4 in concentrated aqueous solution, accurately capturing effects arising from both structural dynamics and electron exchange–correlation. We predict contact-ion-pair formation to be barrierless and highly exoergic for Ca–SO 4 , in agreement with its minimal solubility, whereas for Mg–SO 4 , solvent-shared and contact ion pairs have similar free energies, qualitatively consistent with its higher solubility. Finally, we demonstrate that brief high-temperature pre-equilibration may be utilized to accelerate convergence of free energies in blue-moon-ensemble enhanced-sampling MD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

50 KW Multi-beam Klystron

Statement of problem or situation that is being addressed: microwave power sources (such as klystrons) offering an increased efficiency (80% or above) are needed for various applications. Of a particular interest is a source at 952.6 MHz delivering 50kW (continuous) CW for the RF systems for ion acceleration in the Energy Electron Ion Collider EIC being developed at Thomas Jefferson National Accelerator Facility. General statement of how this problem is being addressed: A novel tube (klystron) concept with efficiency in excess of 80%, delivering 50 kW CW at 952.6 MHz MHz is proposed. It is a combination of proven technologies put together: its uses multiple beams to have its perveance low to boost beam-power to RF efficiency. It uses a partially grounded depressed collector (as invented by Omega P R&D) with a carefully tailored beam distribution after the cavity chain to recover energy thereby increasing the overall efficiency even more. A low operating voltage makes the tube more user-friendly avoiding need for costly modulators and oil insulation. A sectioned solenoid is used to insure superb beam-matching to all components downstream of the electron gun, increasing the tube performances. What is to be done in Phase I: The overall goal of this project is to develop, design, engineer, manufacture and test a multi-beam klystron operating in CW regime, delivering 50kW CW of power at 952.6 MHz. The effort is to be coordinated with TJNAF to insure excellent compatibility with the facility. The device will have a high efficiency >80% (operating at 12kV). The main goals during Phase I are to numerically simulate and optimize the klystron main components, namely the gun, the RF cavity chain, the multi-channel-channel partially grounded depressed collector, and the magnetic system. Preliminary engineering issues will be coordinated by Omega-P R&D with its strategic alliance partner Calabazas Creek Research Inc., which expected to participate formally during Phase II in final design and fabrication. Commercial Applications and Other Benefits: The klystrons of this type can serve as the main RF-energy source of in RF-systems for accelerators which have found their applications both in science and industry, and is of high interest to Thomas Jefferson National Accelerator Facility.

RF power sources, klystron, high efficiency, CW, e↗
DOE OSTI2022

A Feasibility Study on Use of an Accelerometer to Measure the Dynamic Forces in Turning

Metal cutting is a highly dynamic process that generates continuously varying forces. Measurement of these forces is essential to characterizing a cutting process and to fully utilize the machine tool. A force dynamometer is often used to measure these varying forces; however, it is limited by the natural frequency of the sensor and can sometimes be hard to set up on a machine. Therefore, this study aims to estimate the dynamic component of the cutting force using an accelerometer placed directly below the cutting edge. The placement of the sensor helps achieving better signal to noise ratio (S/N). The cutting tool is modelled as a single degree of freedom (SDOF) system relative to the workpiece and dynamic loads are experimentally simulated on it. The measured acceleration is numerically integrated to obtain velocity and deflection, which along with the natural frequency (ω n ) and damping ratio (ζ), is used to predict the dynamic load using the system equation. The dynamic forces tested over a wide range of frequencies, show good agreement with the data from simultaneous dynamometer measurement and the force estimated using the proposed method. The study shows the feasibility of this method in a real cutting scenario and the capability to apply it to a multi DOF system. One major limitation is the inability to capture the static or quasi-static component of the cutting force.

Cutting vibrations↗
DOE OSTI2017

Initial CEED API (CEED-MS10)

Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone, we initiated the development and implementation of a common CEED API consisting of two main components: low-level and high-level APIs. We accomplished the goal of having the low-level component ready for the release of CEED v1.0 in the next quarter, see CEED-MS13. In this report we also provide a highlight from CEED’s integration with the MARBL app and the corresponding Laghos miniapp. A main theme in this work has been the systematic transition of advanced algorithms, developed and tested in Laghos, to the large-scale multi-physics settings of the MARBL code. The low-level CEED API provides a set of FE kernels and components for writing new low-level kernels. Examples include: vector and sparse linear algebra, element matrix assembly over a batch of elements, partial assembly and action for efficient high-order operators like mass, diffusion, advection, etc. The main goal of the low-level API is to establish the basis for the high-level API. Also, identifying such low-level kernels and providing a reference implementation for them serves as the basis for collaboration with vendors and STs. Another goal for the low-level API is to make it easy for applications with their own discretization infrastructure, who do not want to switch directly to using the high-level CEED API, to still evaluate and use the core operations provided by the low-level API. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. Thus, another important question we tried to address while developing the low-level API is: is it possible to abstract out in a natural and efficient way the different implementations and data structures that arise when dealing with various computational device types: CPUs, GPUs, etc. Fully answering this question is beyond the scope of this particular milestone, since that requires longer time as we develop and expand the devices we support. The future high-level API will be the frontend provided by CEED consisting of high-level abstractions such as meshes, finite element spaces and solutions, bilinear forms, solvers, etc. At this high-level, an important aspect of the API will be to provide a uniform abstraction layer for writing code in a portable manner. To achieve that, we plan to utilize the MPI programming model combined with a device abstraction layer (DAL) for finite element computations that we will develop. The DAL will serve as the bridge between the low- and the high-level APIs, allowing a variety of programming models to be used for the low-level kernel implementations. The software artifacts delivered as part of this milestone include an initial CEED API software implementation (libCEED) provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q1 of FY18, including: the Nek5000 v17.0 MFEM v3.3.2 and PETSc v3.8 releases, collaborations with ECP/ST and SciDAC projects, the inaugural Nek5000 hackathon and various outreach activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗
DOE OSTI2019

Miscanthus sinensis multi-location trial: phenotypic analysis, genome-wide association, and genomic prediction

This dataset contains genotypic and phenotypic data, R scripts, and the results of analysis pertaining to a multi-location field trial of Miscanthus sinensis . Genome-wide association and genomic prediction were performed for biomass yield and 14 yield-component traits across six field trial locations in Asia and North America, using 46,177 single-nucleotide polymorphism (SNP) markers mined from restriction site-associated DNA sequencing (RAD-seq) and 568 M. sinensis accessions. Genomic regions and candidate genes were identified that can be used for breeding improved varieties of M. sinensis , which in turn will be used to generate new M. xgiganteus clones for biomass.

genome-wide association studies (GWAS)↗
DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗
DOE OSTI2022

Parthenon—a performance portable block-structured adaptive mesh refinement framework

On the path to exascale the landscape of computer device architectures and corresponding programming models has become much more diverse. While various low-level performance portable programming models are available, support at the application level lacks behind. To address this issue, we present the performance portable block-structured adaptive mesh refinement (AMR) framework Parthenon, derived from the well-tested and widely used Athena++ astrophysical magnetohydrodynamics code, but generalized to serve as the foundation for a variety of downstream multi-physics codes. Parthenon adopts the Kokkos programming model, and provides various levels of abstractions from multidimensional variables, to packages defining and separating components, to launching of parallel compute kernels. Parthenon allocates all data in device memory to reduce data movement, supports the logical packing of variables and mesh blocks to reduce kernel launch overhead, and employs one-sided, asynchronous MPI calls to reduce communication overhead in multi-node simulations. Using a hydrodynamics miniapp, we demonstrate weak and strong scaling on various architectures including AMD and NVIDIA GPUs, Intel and AMD x86 CPUs, IBM Power9 CPUs, as well as Fujitsu A64FX CPUs. At the largest scale on Frontier (the first TOP500 exascale machine), the miniapp reaches a total of 1.7 × 10 13 zone-cycles/s on 9216 nodes (73,728 logical GPUs) at [Formula: see text] weak scaling parallel efficiency (starting from a single node). In combination with being an open, collaborative project, this makes Parthenon an ideal framework to target exascale simulations in which the downstream developers can focus on their specific application rather than on the complexity of handling massively-parallel, device-accelerated AMR.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Stealthy Cyber Anomaly Detection On Large Noisy Multi-material 3D Printer Datasets Using Probabilistic Models

As Additive Layer Manufacturing (ALM) becomes pervasive in industry, its applications in safety critical component manufacturing are being explored and adopted. However, ALM's reliance on embedded computing renders it vulnerable to tampering through cyber-attacks. Sensor instrumentation of ALM devices allows for rigorous process and security monitoring, but also results in a massive volume of noisy data for each run. As such, in-situ, near-real-time anomaly detection is very challenging. The ideal algorithm for this context is simple, computationally efficient, minimizes false positives, and is accurate enough to resolve small deviations. In this paper, we present a probabilistic-model-based approach to address this challenge. To test our approach, we analyze current measurements from a polymer composite 3D printer during emulated tampering attacks. Our results show that our approach can consistently and efficiently locate small changes in the presence of substantial operational noise.

Yoginath, Srikanth↗
DOE OSTI2019

Hierarchical Multi-scale Modeling of Laser Weld Failure: An Initial Investigation

The failure of 304L laser welds is of interest to system and component designers due to nuclear safety requirements for abnormal environments. Accurately modeling laser weld behavior in full system and component models has proven especially challenging due to three factors: the large variability observed in laser weld characterization tests; the difficulty in isolating the weld material for material characterization and modeling the weld material behavior; and the disparate scales associated with modeling laser welds in large systems. Recent work has shown that meso-scale geometric features of laser welds such as pores and weld root tortuosity are critical to accurately predicting the structural performance of welds. The challenge with modeling these welds is that the geometric features driving their structural performance are generally on the order of ten to hundreds of microns, but can affect the responses of interest in systems and components on the order of centimeters to meters.

36 MATERIALS SCIENCE↗