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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Impact of Varying Dark Energy on Future Large-Scale Structure Studies

The cosmos withholds multiple mysteries such as dark forms of matter and energy that are yet beyond human comprehension. In the standard cosmological model, $\Lambda$CDM, the cosmological constant $\Lambda$ is thought to be responsible for the late accelerated expansion of the Universe. However, recent results from the Dark Energy Spectroscopic Instrument (DESI) suggest the possibility of evolving dark energy, which warrants further exploration. Future surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST) will map the large-scale structure (LSS) with unprecedented precision, giving us valuable statistical information about the cosmos. The goal of this research is to investigate the potential impact of an evolving dark energy scenario on cosmological parameters constrained by LSS probes, as will be mapped by the LSST. For this, we examine the power spectra of lens galaxies, source galaxies, and cross-power spectra between lens galaxies and source galaxies. The combination of these statistics is commonly referred to as '3 $\times$ 2 points'. For this investigation, we created a set of simulations resembling LSST data and used them to perform cosmological parameter inference in two scenarios: one in which the simulated data is based on the fiducial model and another on evolving dark energy. We then examined the degeneracy between the cosmological parameters and checked for potential shifts in the parametric space when the data contains dynamical dark energy but the modeling assumes $\Lambda$CDM. Our findings indicate that mismodeling the dark energy equation of state can significantly impact parameter inference, particularly affecting the total matter density, $\Omega_m$, and the growth of structures, as represented by the $S_8$ parameter. These results highlight the importance of further exploring extensions of the $\Lambda$CDM model in future LSS studies.

Yaman Acharya, A.↗
DOE OSTI2024

Large-scale Structure of the Heliospheric Current Sheets within the Heliosheath Inferred from Voyager 2 Observations

In this paper, we conducted an analysis of the heliospheric current sheets (HCSs) in the heliosheath (HS), utilizing observations by Voyager 2 between 2008 and 2018. Employing rigorous criteria, we identified a total of 34 HCSs that indicate significant changes in magnetic polarity. These occurrences were more prevalent during solar maximum periods when the HCS expanded to higher latitudes, coinciding with the spacecraft positioned at an average latitude of –31° from the solar equator. We determined certain features of the large-scale structures of the identified HCSs. Most importantly, employing two distinct methods indicates that the thickness of the HCSs within the HS ranges from ~0.003 to ~0.4 au with an average thickness of ~0.03 to ~0.1 au, depending on methods of event selection and fitting techniques. This thickness surpasses that known near 1 au or other heliospheric distances. It is also notably thicker than the typical proton inertial length, implying unfavorable conditions for magnetic reconnection. Additionally, our analysis reveals a frequent tilt of HCS planes relative to the solar equatorial plane by a varying angle up to several tens of degrees, likely implying a common occurrence of a warped structure of the HCS within the HS. Longitudinally, the HCS planes closely align with the Parker spiral field direction expected in the HS. Finally, for a large fraction of the identified HCS events, the HCS planes are likely characterized by a rotational discontinuity. These findings are valid within the limits of the 1 hr resolution data used in this study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Large-Scale Analysis to Optimize the Control and V2V Communication Protocols for CDA Agreement-Seeking Cooperation

Cooperative driving automation (CDA) Class C, agreement-seeking cooperation, is an innovative and practical solution that can promote cooperation among general passenger vehicles on the road. However, more comprehensive studies are needed before establishing the standard protocols of agreement-seeking cooperation, such as communication frequency and the duration of cooperation. Here, this article presents an initiative study on the impacts of communication capabilities on agreement-seeking cooperation. Through a large-scale analysis by regulating vehicle-to-vehicle (V2V) communication metrics, this work suggests desirable system parameters that can maximize the benefits of cooperation and ensure reliable operability while avoiding exhaustive communication loads. As the first step, an example agreement-seeking cooperation system is created for a car-following scenario, including decision-making and control algorithms for autonomous vehicles. Then, software-in-the-loop tests explore the performance of the developed system as it encounters various communication risks, such as latency and message packet drops. The system performance metrics are evaluated from various angles, including the time consumed for the agreement-seeking process, cooperation ratio, and the ratio of faulty cooperation. Energy saving from the cooperation is assessed by using simulation software that can run multiple high-fidelity vehicle models simultaneously. Based on the analyses, this article suggests the V2V communication requirements for the reliable operation of CDA agreement-seeking, which can be referred to when developing the standard protocols of agreement-seeking cooperation.

42 ENGINEERING↗
DOE OSTI2024

Addressing the data and real-time challenges in large scale particle physics experiments through AI and in situ computing technologies

Modern high energy physics experiments are faced not only with the challenge of having to deal with extremely high data rates but with the need to process data quickly to meet real time constraints. At Fermilab, we explore the use of novel computing technologies and techniques to address these challenges. I will discuss my R&D efforts in applying such computing solutions to enhance the multi-messenger astronomy capabilities and improve the overall physics performance of large-scale LArTPC based neutrino experiments. These efforts offer excellent opportunities for fruitful collaboration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗
DOE OSTI2020

Measurement of DC Arc-Flash Incident Energy in Large-Scale Photovoltaic Plants: A Basis for Standardization

The deployment of high-power dc equipment is increasing in solar photovoltaic (PV) plants, but very few studies have quantified dc arc-flash risks. Currently, PV plant owners and operators rely on theoretical, simplified models, such as those in NFPA-70E and other publications, for the assessment of risk associated with dc arc-flash. Here, this article presents an overview of arc-flash risks in a PV system based on a series of field experiments based on IEEE-1584 in two large-scale ground-mounted PV plants. The experiments include various high-power dc equipment of a PV plant, such as central inverters, combiner boxes, recombiner boxes, string inverters, and multiple configurations of electrodes in a 20-in calibration cube. The study reveals that none of the available dc arc-flash models are applicable for a PV plant. This work is an important first step toward developing an improved model that more accurately assesses dc arc-flash risk in a PV plant.

14 SOLAR ENERGY↗
DOE OSTI2023

Large-scale Evolution of Seconds-long Relativistic Jets from Black Hole–Neutron Star Mergers

We present the first numerical simulations that track the evolution of a black hole–neutron star (BH–NS) merger from premerger to r ≳ 10 11 cm. The disk that forms after a merger of mass ratio q = 2 ejects massive disk winds (3–5 × 10 –2 M ⊙ ). We introduce various postmerger magnetic configurations and find that initial poloidal fields lead to jet launching shortly after the merger. The jet maintains a constant power due to the constancy of the large-scale BH magnetic flux until the disk becomes magnetically arrested (MAD), where the jet power falls off as L j ~ t –2 . All jets inevitably exhibit either excessive luminosity due to rapid MAD activation when the accretion rate is high or excessive duration due to delayed MAD activation compared to typical short gamma-ray bursts (sGRBs). This provides a natural explanation for long sGRBs such as GRB 211211A but also raises a fundamental challenge to our understanding of jet formation in binary mergers. One possible implication is the necessity of higher binary mass ratios or moderate BH spins to launch typical sGRB jets. For postmerger disks with a toroidal magnetic field, dynamo processes delay jet launching such that the jets break out of the disk winds after several seconds. We show for the first time that sGRB jets with initial magnetization σ0 > 100 retain significant magnetization (σ $\gg$ 1) at r > 10 10 cm, emphasizing the importance of magnetic processes in the prompt emission. The jet–wind interaction leads to a power-law angular energy distribution by inflating an energetic cocoon whose emission is studied in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Model of Large Scale Electrochemical Direct Ocean Capture Under Variable Power

Since limiting warming to 1.5 degrees C by 2100 will not only require an energy transition but also billions of tons of carbon dioxide (CO2) removal per year, it is essential to expand these efforts. This can be done offshore via electrochemical direct ocean capture (eChem DOC) which extracts CO2 from seawater that can later be stored underground or converted to products. Deployments of eChem DOC will be powered by renewable energy and therefore need to function with variable power inputs. This project aims to support future large-scale deployments by developing a model of eChem DOC operation, informed by industry and literature, and assessing its performance under variable power and varying designs. Initial analysis suggests that discretizing the eChem system has a higher impact on increasing overall capture than storing the chemical solutions to continue capture during periods of lower power availability, but this is likely situation dependent. Future work will use more realistic power profiles.

direct ocean capture↗
DOE OSTI2020

An overview of the Energy Modeling Forum 33rd study: Assessing large-scale global bioenergy deployment for managing climate change

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2°C or 1.5°C. However, with significant variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University’s Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run, biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research.

Rose, Steven K.↗
DOE OSTI2022

Large-Scale Interlaboratory DI-FT-ICR MS Comparability Study Employing Various Systems

We report ultra-high resolution mass spectrometry (UHR-MS) coupled with direct infusion (DI) electrospray ionization offers a fast solution for accurate untargeted profiling. Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers have been shown to produce a wealth of insights into complex chemical systems because they enable unambiguous molecular formula assignment even if the vast majority of signals is of unknown identity. Inter-laboratory comparisons are required to apply this type of instrumentation in quality control (for food industry or pharmaceutics), large-scale environmental studies or clinical diagnostics. Extended comparisons employing different FT-ICR MS instruments with qualitative direct infusion analysis are scarce since the majority of detected compounds cannot be quantified. The extent to which observations can be reproduced by different laboratories remains unknown. We set up a preliminary study which encompassed a set of seventeen laboratories around the globe, diverse in instrumental characteristics and applications, to analyze the same sets of extracts from commercially available standard human blood plasma and Standard Reference Material (SRM) for blood plasma (SRM1950), which were delivered at different dilutions or spiked with different concentrations of pesticides. The aim of this study was to assess the extent to which the outputs of differently tuned FTICR mass spectrometers, with different technical specifications, are comparable for setting the frames of a future DI-FT-ICR MS ring trial. We concluded that a cluster of five laboratories, with diverse instrumental characteristics showed comparable and representative performance across all experiments, setting a reference to be used in a future ring trial on blood plasma.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding

Abstract Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million technical drawings with 132,890 object names and 22,394 viewpoints extracted from 14 years of US design patent documents. We demonstrate the usefulness of DeepPatent2 with conceptual captioning. We further provide the potential usefulness of our dataset to facilitate other research areas such as 3D image reconstruction and image retrieval.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

In-Situ Monitoring Assisted Large-Scale Additive Manufacturing of Mild Steel and 316L Alloys for Nuclear Application

The Advanced Materials and Manufacturing Technologies (AMMT) Program is aimed at developing cross-cutting technologies in support of a broad range of nuclear reactor parts, and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of the AMMT program is to accelerate the development, qualification, demonstration and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. One of its three goals is to target big challenges and game-changing technologies, to realize the mission and vision of AMMT program. Based on this context, this multi-year work package focuses on understanding the current state of large-scale additive manufacturing (AM) technology for the deposition of 316L stainless steel materials for final components and mild steel for use in nuclear manufacturing processes. The targeted AM modality is directed energy deposition (DED), capable of fabricating components on the size scale of meters including valves, pumps, impellers. etc. that are challenging or difficult to source, especially when developing new systems or replacing obsolete components. Accordingly, the current writeup aims at providing a baseline literature survey on structure-property relationships in mild steel and 316L alloys. Also, information on preliminary trials to date involving these two alloys show tremendous potential of printing parts having complex geometry and thin- walled structures, such as nuclear valve and Hot isostatic Press (HIP) can, using wire based (Wire Arc Additive Manufacturing and Hybrid Additive Manufacturing) as well as blown powder DED machines. All of this is aimed towards (i) demonstrating the ability to fabricate large components for pressure boundary applications relevant to the nuclear community and nuclear manufacturing technology, and (ii) understanding the effect of different manufacturing technology on AM can production and post HIPed material for nuclear applications. Another target of this writeup is to compile various in-situ monitoring tools that have been incorporated for different DED AM modalities, in order to understand process variability during the entire fabrication process. This can be correlated with processing-structure-property response surfaces and would add confidence around process quality verification and ultimately component certification for nuclear applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Study of interconnect errors, network congestion, and applications characteristics for throttle prediction on a large scale HPC system

Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Benchmark for two-dimensional large scale coherent structures in partially magnetized E × B plasmas—community collaboration & lessons learned

Low-temperature plasmas (LTPs) are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark benchmark initiative, a series specifically designed to support the verification of LTP codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized E × B Penning discharge. The emergence of large scale coherent structures, or rotating plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key plasma properties, including time-averaged ion density, plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future plasma simulation software development.

benchmarking↗
DOE OSTI2022

Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs

Abstract Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Large-scale real-time signal processing in physics experiments: the ALICE TPC FPGA pipeline

For LHC Run 3, the ALICE Time Projection Chamber was upgraded to operate in continuous readout mode. Interaction rates of up to 50 kHz in Pb-Pb collisions require real-time processing of more than 3 TB s -1 of raw detector data. This requirement is met by a custom FPGA-based processing pipeline that performs the complete front-end data treatment fully in-stream, including common-mode correction, pedestal subtraction, ion-tail filtering, zero suppression, and dense data packing. A central element of the design is a highly parallel common-mode correction algorithm operating directly on the streaming data. It robustly identifies signal-free readout channels on a time-bin basis and applies pad-dependent scaling to compensate for local variations in capacitive coupling in the GEM readout. In combination with pedestal subtraction and ion-tail filtering, this enables accurate baseline restoration under extreme high-occupancy conditions, preventing signal loss while efficiently suppressing noise prior to zero suppression. The pipeline operates continuously at the full detector bandwidth and reduces the raw input rate of approximately 3 TB s -1 to about 900 GBps for Pb-Pb collisions at the target interaction rate. Overall, it represents a large-scale FPGA-based real-time signal-processing implementation for high-energy physics detector readout.

Digital signal processing (DSP)↗