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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optics Studies for Multipass Energy Recovery at CEBAF: ER@CEBAF

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson Lab focuses on demonstrating highest energy recovery in super conducting linac in the low-current range. Continuous electron beam accelerate up to 7.5 GeV within 5-passes and decelerate in the next 5-passes recovering RF energy and dumps at a low energy dump. The beamline optics design for recirculating linacs require special attention to avoid beam instabilities due to RF wakefields. Usually, multi-pass linac beam lines require stronger focusing at lower energies as that is necessary to avoid beam breakup (BBU) instabilities, even with this small beam current. The CEBAF linac optics optimization is focused on balancing over-focusing at higher energies and beta excursions at lower energies. The race-track-shaped geometry of CEBAF accelerator allows its linacs to accommodate multiple energy beams simultaneously, while individual recirculating arcs transporting one beam energy, are shared between accelerating/decelerating beams. For the linac optics optimization process, an extended strategy is used that is originally used in 6-pass Recirculating Linac design of the LHeC, to represent the ten passes through a single linac. Using proper mathematical expressions, linac optics optimization can be achieved with evolutionary genetic algorithms, with Multi-Objective optimization. This thesis introduces a CEBAF optics redesign tailored to accommodates the ER@CEBAF multi-pass ER scheme. The isochronous arcs were retuned to match into optics solutions for optimized 10-pass linacs. Within this work, a single bunch particle tracking analysis presented here focuses on the further improvements of the beamline and beam transportation.

Neththikumara, Isurumali↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2022

Enabling cooperative adaptive cruise control on strings of vehicles with heterogeneous dynamics and powertrains

Recent studies have shown that positive impact of Cooperative Adaptive Cruise Control (CACC) can only be guaranteed as market penetration rate increases. Removing the string homogeneity constraint is essential to encourage widespread adoption. In this work, a hierarchical architecture is proposed to enable CACC on vehicles with not only mixed dynamics but also different powertrain types. A low-level layer deals with the vehicle and powertrain dynamics to provide accurate and consistent reference speed tracking response. The high-level layer uses: (1) a Linear Parameter Varying feedback system to provide loop stability, robustness and enforce a variable time gap policy and (2) a feedforward system that processes Vehicle-to-Vehicle information to enhance string stability and response bandwidth, by dealing with the string heterogeneity. A gap management strategy is built on top of the CACC architecture to handle gap setting changes or cut-in/out situations, via a dynamics constrained time gap trajectory planning algorithm. We report the proposed work has been designed, developed and validated on three different real passenger vehicles on public highways and test tracks, showing the potential of the proposed algorithm to enable robust string stable CACC, despite the different dynamics and powertrains considered.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Elastic-wave sensitivity-guided adaptive seismic survey design for cost-effective monitoring of geological carbon storage

Effective seismic monitoring is essential for verifying CO₂ containment, detecting potential leakage, and optimizing operational decisions in geologic carbon storage. Here, this study presents a time-adaptive, elastic-wave sensitivity-guided framework for designing cost-effective seismic monitoring layouts for tracking CO₂ plume migration. The method is based on elastic-wave sensitivity analysis, which quantifies how variations in subsurface properties impact seismic wavefields. Two complementary design strategies are developed: one based on selecting a fixed number of seismic sources (Method A), and the other based on selecting source–receiver pairs contributing to a fixed fraction of cumulative elastic-wave sensitivity energy (Method B). The optimization workflow to identify source–receiver configurations with the highest detection potential is demonstrated using a hypothetical GCS scenario at the Kimberlina site in California using simulations of elastic-wave sensitivity data at multiple post-injection timesteps. Results show that both strategies adapt to evolving plume geometries and wavefield sensitivities, with Method B offering broader spatial coverage and Method A ensuring simpler deployment. This framework enables site-specific, cost-effective, and risk-informed seismic survey designs, enhancing the ability to monitor CO₂ migration over time in evolving geological environments

58 GEOSCIENCES↗
DOE OSTI2021

Wake Steering Wind Farm Control With Preview Wind Direction Information: Preprint

Wake steering is a wind farm control strategy in which upstream turbines operate with a yaw misalignment to deflect their wakes away from downstream turbines, yielding a net power gain for the wind plant. But the inability of wake steering controllers to perfectly track the wind direction leads to suboptimal performance. In this paper, we propose the use of preview wind direction measurements upstream of the turbine to improve controller performance by anticipating wind direction changes. Further, data from an operational wind plant are used to determine realistic preview measurement accuracy. Using the FLORIS engineering wind farm control tool, we compare the performance of standard and preview-enabled baseline and wake steering control for a two-turbine array during below-rated operation. Assuming perfect preview information, preview-based wake steering increases energy production by the equivalent of 9.5% of the baseline wake losses, compared to a wake loss recovery of 5.6% with standard wake steering. However, when realistic measurement accuracy is included, the preview-based controller provides no advantage over standard control, motivating the need for more sophisticated control and wind direction forecasting strategies.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
DOE OSTI2021

Controlled Organization of Inorganic Materials Using Biological Molecules for Activating Therapeutic Functionalities

Precise control over the assembly of biocompatible three-dimensional (3D) nanostructures would allow for programmed interactions within the cellular environment. Nucleic acids can be used as programmable crosslinkers to direct the assembly of quantum dots (QDs) and tuned to demonstrate different interparticle binding strategies. In this work, morphologies of self-assembled QDs are evaluated via gel electrophoresis, transmission electron microscopy, small-angle X-ray scattering, and dissipative particle dynamics simulations, with all results being in good agreement. The controlled assembly of 3D QD organizations is demonstrated in cells via the colocalized emission of multiple assembled QDs, and their immunorecognition is assessed via enzyme-linked immunosorbent assays. RNA interference inducers are also embedded into the interparticle binding strategy to be released in human cells only upon QD assembly, which is demonstrated by specific gene silencing. The programmability and intracellular activity of QD assemblies offer a strategy for nucleic acids to imbue the structure and therapeutic function into the formation of complex networks of nanostructures, while the photoluminescent properties of the material allow for optical tracking in cells in vitro.

36 MATERIALS SCIENCE↗
DOE OSTI2022

DefectTrack: a deep learning-based multi-object tracking algorithm for quantitative defect analysis of in-situ TEM videos in real-time

Abstract In-situ irradiation transmission electron microscopy (TEM) offers unique insights into the millisecond-timescale post-cascade process, such as the lifetime and thermal stability of defect clusters, vital to the mechanistic understanding of irradiation damage in nuclear materials. Converting in-situ irradiation TEM video data into meaningful information on defect cluster dynamic properties (e.g., lifetime) has become the major technical bottleneck. Here, we present a solution called the DefectTrack , the first dedicated deep learning-based one-shot multi-object tracking (MOT) model capable of tracking cascade-induced defect clusters in in-situ TEM videos in real-time. DefectTrack has achieved a Multi-Object Tracking Accuracy (MOTA) of 66.43% and a Mostly Tracked (MT) of 67.81% on the test set, which are comparable to state-of-the-art MOT algorithms. We discuss the MOT framework, model selection, training, and evaluation strategies for in-situ TEM applications. Further, we compare the DefectTrack with four human experts in quantifying defect cluster lifetime distributions using statistical tests and discuss the relationship between the material science domain metrics and MOT metrics. Our statistical evaluations on the defect lifetime distribution suggest that the DefectTrack outperforms human experts in accuracy and speed.

42 ENGINEERING↗
DOE OSTI2021

A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries

Herein, we present a computational framework for solving the equations of inviscid gas dynamics using structured grids with embedded geometries. The novelty of the proposed approach is the use of high-order discontinuous Galerkin (dG) schemes and a shock-capturing Finite Volume (FV) scheme coupled via an hp adaptive mesh refinement (hp-AMR) strategy that offers high-order accurate resolution of the embedded geometries. The hp-AMR strategy is based on a multi-level block-structured domain partition in which each level is represented by block-structured Cartesian grids and the embedded geometry is represented implicitly by a level set function. The intersection of the embedded geometry with the grids produces the implicitly-defined mesh that consists of a collection of regular rectangular cells plus a relatively small number of irregular curved elements in the vicinity of the embedded boundaries. High-order quadrature rules for implicitly-defined domains enable high-order accuracy resolution of the curved elements with a cell-merging strategy to address the small-cell problem. The hp-AMR algorithm treats the system with a second-order finite volume scheme at the finest level to dynamically track the evolution of solution discontinuities while using dG schemes at coarser levels to provide high-order accuracy in smooth regions of the flow. On the dG levels, the methodology supports different orders of basis functions on different levels. The space-discretized governing equations are then advanced explicitly in time using high-order Runge-Kutta algorithms. Numerical tests are presented for two-dimensional and three-dimensional problems involving an ideal gas. The results are compared with both analytical solutions and experimental observations and demonstrate that the framework provides high-order accuracy for smooth flows and accurately captures solution discontinuities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Intracellular Biomacromolecule Delivery by Stimuli-Responsive Protein Vesicles Loaded by Hydrophobic Ion Pairing

Proteins can perform ideal therapeutic functions. However, their large size and significant surface hydrophilicity and charge prohibit them from reaching intracellular targets. These chemical features also render them poorly encapsulated by nanoparticles used for intracellular delivery. In this work, a novel combination of protein vesicles and hydrophobic ion pairing (HIP) was used to load protein cargo and achieve cytosolic delivery to overcome the limitations of previous protein vesicle properties. Protein vesicles are thermally self-assembling nanoparticles made from elastin-like polypeptide (ELP) fused to an arginine-rich leucine zipper and a globular protein fused to a glutamate-rich leucine zipper. To impart stimuli-responsive disassembly, physiological stability, and small size, the ELP sequence was modified to include histidine and tyrosine residues. HIP was used to load and release protein cargo requiring endosomal escape for cytosolic function. HIP vesicles enabled delivery of cytochrome c, a cytosolically active protein, and a significant reduction in viability in both a traditional two-dimensional (2D) human cancer cell line culture and a biomimetic three-dimensional (3D) organoid model of acute myeloid leukemia. By examining the uptake of positively and negatively charged fluorescent protein cargos loaded by HIP, this work revealed the necessity of HIP for cytosolic cargo delivery and how HIP loading influences protein vesicle self-assembly and disassembly using microscopy, small-angle X-ray scattering, and nanoparticle tracking analysis. HIP protein vesicles have the potential to broaden the use of intracellular proteins as therapeutics for various diseases and extend protein vesicles to deliver other biomacromolecules, as the strategy developed here resulted in the first cytosolic protein cargo delivery using protein vesicles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cyber‐Resilient Distributed Energy Resource Control Algorithms for Smart Distribution Grids

ABSTRACT This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid‐interactive distributed energy resource (DER) control to enable two grid services of virtual power plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. Firstly, the combined DER dispatch and voltage regulation as a real‐time gradient‐based optimisation problem is recapped. Thereafter, we consider a probabilistic traffic model to characterise packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control centre that execute this control algorithm in a coordinated manner. Then, a strategy combining delay thresholds and message update rules is proposed to immunity the asynchrony resulting from the communications traffic and it avoids possible numerical instabilities and sensitivities of the power tracking and voltage regulation capabilities, resulting as cyber‐resilient DER control algorithms. Additionally, their convergence is theoretically proved. Effectiveness of proposed cyber‐resilient algorithms has been validated on the IEEE 37‐bus system in terms of convergence, VPP tracking and voltage regulation performance for smart distribution systems with high penetration of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Determination of Carbon, Hydrogen, Nitrogen, and Oxygen in Bio-Oils: Laboratory Analytical Procedure (LAP)

The determination of total carbon, hydrogen, and nitrogen in bio-oils is important as these values can be used to track the carbon balance of production processes as well as calculate total oxygen content by difference. Oxygen content of bio-oils is a key metric for production and upgrading strategies as these are typically aimed at reducing oxygen. Oxygenates in bio-oils contribute to poor hydrocarbon miscibility, high acidity, high viscosity, and poor stability. Upgrading of bio-oils via deoxygenation produces hydrocarbons which can be used to generate feedstocks for renewable fuels and chemicals. In this Laboratory Analytical Procedure (LAP), combustion-based ultimate analysis is used to determine the weight percent (wt%) of C, H, and N in bio-oils and upgraded products. Ultimate analysis uses high temperatures and a pure oxygen environment to completely combust organic samples to carbon dioxide (CO 2 ), water (H 2 O), and nitrogen oxides (NO x ). In this procedure the amount of C and H in the sample are quantified by measuring resultant CO 2 and H 2 O with Fourier-transform infrared spectroscopy (FTIR). For N, NO x is reduced to nitrogen (N 2 ) which is measured with a thermal conductivity detector (TCD), providing total N content.

09 BIOMASS FUELS↗
DOE OSTI2022

Structural basis of R-loop recognition by the S9.6 monoclonal antibody

R-loops are ubiquitous, dynamic nucleic-acid structures that play fundamental roles in DNA replication and repair, chromatin and transcription regulation, as well as telomere maintenance. The DNA-RNA hybrid–specific S9.6 monoclonal antibody is widely used to map R-loops. Here, we report crystal structures of a S9.6 antigen-binding fragment (Fab) free and bound to a 13-bp hybrid duplex. We demonstrate that S9.6 exhibits robust selectivity in binding hybrids over double-stranded (ds) RNA and in categorically rejecting dsDNA. S9.6 asymmetrically recognizes a compact epitope of two consecutive RNA nucleotides via their 2'-hydroxyl groups and six consecutive DNA nucleotides via their backbone phosphate and deoxyribose groups. Recognition is mediated principally by aromatic and basic residues of the S9.6 heavy chain, which closely track the curvature of the hybrid minor groove. These findings reveal the molecular basis for S9.6 recognition of R-loops, detail its binding specificity, identify a new hybrid-recognition strategy, and provide a framework for S9.6 protein engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cyber Physical Grid-Interactive Distributed Energy Resources Control for VPP Dispatch and Regulation

This paper presents a cyber-physical algorithm for grid-interactive Distributed Energy Resource (DER) control to enable two features of Virtual Power Plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. We first formulate the DER dispatch problem as a real-time, iterative, and grid-interactive DER control problem. Thereafter, we consider a probabilistic traffic model to characterize packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control center that coordinately execute this dispatch algorithm. Finally, a strategy combining delay threshold and modified message update rules is proposed to immune the asynchrony resulting from the communications network traffic and it avoids possible numerical instabilities and sensitivities of the tracking and regulation capabilities of this DER control algorithm. By implementing the proposed cyber-physical algorithm on the modified IEEE 37-node system, our preliminary results exhibit that the uncertainties of the underlying communications infrastructure must be considered for the VPP tracking and regulation capabilities of any DER in a generic Cyber-Physical System (CPS), because the delayed voltage measurements in the uplink/bi-link cases result in the off-track in VPP dispatch and jittery in voltage regulation.

cyber-physical algorithm↗
DOE OSTI2024

An Update on Project PARETO - New Capabilities in DOE's Produced Water Optimization Framework

Managing oil and gas produced water, characterized by hypersalinity and large volumes, presents significant challenges. This paper introduces an advanced optimization framework, PARETO, which offers a novel approach to strategic water management, emphasizing produced water (PW) treatment, quality tracking, quantification of emissions, and environmental justice. This work pre-sents a case study showcasing different produced water management challenges. The PARETO framework demonstrated its effectiveness in optimizing water management strategies in line with environmental sustainability and regulatory compliance.

Zamarripa, Miguel↗
DOE OSTI2024

SRNL Nuclear Material Management Strategy

Started in FY22 to categorize with the goal of determining assets and liabilities for the new management team and reducing SRNL’s excess inventory. • Allow for program growth within the current material limits. • Prior to FY22 inventory was a ‘blackbox’. • No formal system for tracking utilization or future needs until items arrived. • Created friction between management and researchers • Slowed down incoming projects • Risk of breaking safety and/or security limits • Risk of jepardizing program growth.

Ramsey, Catherine M.↗
DOE OSTI2021

Testing at scale during the COVID-19 pandemic

Assembly and publication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome in January 2020 enabled the immediate development of tests to detect the new virus. This began the largest global testing programme in history, in which hundreds of millions of individuals have been tested to date. The unprecedented scale of testing has driven innovation in the strategies, technologies and concepts that govern testing in public health. In this Review, we describe the changing role of testing during the COVID-19 pandemic, including the use of genomic surveillance to track SARS-CoV-2 transmission around the world, the use of contact tracing to contain disease outbreaks and testing for the presence of the virus circulating in the environment. Despite these efforts, widespread community transmission has become entrenched in many countries and has required the testing of populations to identify and isolate infected individuals, many of whom are asymptomatic. The diagnostic and epidemiological principles that underpin such population-scale testing are also considered, as are the high-throughput and point-of-care technologies that make testing feasible on a massive scale.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance

The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.

Maldonado Puente, Bryan↗