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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Hanford Double Shell Tank Integrity Inspection - Integration of Customized Robotics - 18400

28 steel, double-shell, million gallon waste storage tanks located at the Hanford site in Washington State store both radioactive and hazardous waste. To monitor their condition and ensure continued viability, these tanks are inspected periodically through a comprehensive integrity program. In 2012, the first leak in a double-shell tank at Hanford was discovered in the 241-AY tank farm (Tank AY-102) and the failure was observed to be from the primary tank bottom. However, the exact failure location and damage mechanism have not been determined. A decision was made to pursue the capability to inspect the primary tank bottom region in order to provide additional tank integrity information. This work is particularly challenging due to the confined space in the double-shell tank annulus region (i.e. the 30 inch space between the primary and secondary tank shells), the limited dimensions of the tank risers that provide access to the annulus space (risers as small as 10 inches in diameter), and also the very small dimensions of the air channels in the concrete refractory pad that the primary waste storage tank rests on (channels are approximately two inches in diameter). Veolia Nuclear Solutions, along with Key Subcontractor Inuktun, were contracted to provide the capability to conduct these tank inspections in support of Hanford's double-shell tank integrity program. The Veolia Nuclear Solutions /Inuktun team designed, built, tested and delivered a tethered miniature robotic crawler system that utilizes the marsupial approach - a larger deployment crawler positions a smaller inspection crawler. The deployment crawler is installed via the tank riser, is magnetically coupled to the side of the tank shell, and drives to the selected deployment location at the end of one of the refractory channels where the small inspection robot is subsequently deployed. Operation of the equipment is controlled from a trailer outside the tank farm (a distance of several hundred feet). The system design includes a custom mechanism that provides for positioning and cable handling as well as the controls interface (laptop connected via control cables). The solution leveraged the Veolia Nuclear Solutions/Inuktun team's experience with delivering similar modular systems for other US and international sites. This simple but innovative solution delivered on an accelerated project schedule underlines the ability to provide effective robotic solutions to the nuclear industry. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

SU-C-BRB-05: Determining the Adequacy of Auto-Contouring Via Probabilistic Assessment of Ensuing Treatment Plan Metrics in Comparison with Manual Contours

Purpose: To determine if auto-contour and manual-contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT. Methods: Manual and auto-contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto-contouring was completed utilizing Pinnacle’s Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7-beam IMRT plans are created; PD with drawn ROIs, PAS with auto-contoured ROIs, and PM with auto-contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampled systematic errors for each simulation and a different sampled random error for each fraction were performed using our in-house GPU-accelerated robustness analyzer tool which reports the statistical probability of achieving dose-volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto-contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross-evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose-volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D-PD). Results: We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV’s D95 and Dmin objectives are small for AS-PM, AS-PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS-PM, AS-PD sustain variations up to %6 compared to other evaluated pairs. Conclusion: No significant probabilistic differences are observed in the metrics when auto-contoured OARs are used. The prostate auto-contour needs improvement to achieve clinically equivalent plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Graph-Based Modeling for the Detection and Tracking of Sarin-Surrogate-Induced Neurotoxicity Using a Human-Relevant, In-Vitro Brain Model

Organophosphorus (OP) nerve agents are a chemical threat to the United States, to the civilian population (e.g., pesticides) and historically weaponized (e.g., sarin) as chemical warfare agents. The unprecedented, accelerated process from “bench-to-bedside” during the SARSCov2 pandemic has made it clear that technology and tools need to be readily available for immediate response. Advances in human organ tissue mimetic systems are a promising technology to evaluate the human-relevant response in vitro for basic and applied research and drug screening. In particular, current brain microphysiological systems (MPS) have the capability to monitor and detect changes in engineered human neural circuit activity. However, current data analytics approaches for these systems lack the granularity to functionally detect and distinguish the different mechanisms that occur in the brain following neurotoxicity, injury, and disease. The goal of this project was to advance the computational analytical capabilities of the brain MPS to detect functional changes in neural circuit structure at different stages of Sarin surrogate-induced neurotoxicity. We developed graph-based models to (1) identify the composition of the neural circuit structure; (2) detect and monitor how this structure changes following sarin-induced neurotoxicity; and (3) evaluate the analytical pipeline using known/promising oxime reactivators. Through experiments on the bMPS where in vitro neuronal cultures were exposed to a sarin surrogate, we demonstrated the capabilities of our computational pipeline to identify different responses in the functional networks of brain cells exposed to low and high concentrations of the nerve agent. We identified a biphasic response of human neural network activity following exposure to a sarin-surrogate that had not been reported in the literature before. The graph-based models and software developed in this project can be used for future studies that leverage the brain MPS technology, such as treatment efficacy assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Utilizing the unique charge extraction properties of antimony tin oxide nanoparticles for efficient and stable organic photovoltaics

Simultaneously enhancing device performance and longevity, as well as balancing the requirements on cost, scalability, and simplification of processing, is the goal of interface engineering of organic solar cells (OSCs). In our work, we strategically introduce antimony (Sb 3+ ) cations into an efficient and generic n-type SnO 2 nanoparticles (NPs) host during the scalable flame spray pyrolysis synthesis. Accordingly, a significant switch of conduction property from an n-type character to a p-type character is observed, with a corresponding shift in the work function (WF) from 4.01 ± 0.02 eV for pristine SnO 2 NPs to 5.28 ± 0.02 eV for SnO 2 NPs with 20 mol. % Sb content (ATO). Both pristine SnO 2 and ATO NPs with fine-tuned optoelectronic properties exhibit remarkable charge carrier extraction properties, excellent UV resistance and photo-stability being compatible with various state-of-the-art OSCs systems. The reliable and scalable pristine SnO 2 and ATO NPs processed by doctor-blading in air demand no complex post-treatment. Our work offers a simple but unique approach to accelerate the development of advanced interfacial materials, which could circumvent the major existing interfacial problems in solution-processed OSCs.

14 SOLAR ENERGY↗
DOE OSTI2023

Accelerating the development of a sustainable bioenergy portfolio through stable isotopes

Bioenergy could help limit global warming to 2°C above pre-industrial levels while supplying almost a fourth of the world's renewable energy needs by 2050. However, the deployment of bioenergy raises concerns that adoption at meaningful scales may lead to unintended negative environmental consequences. Meanwhile, the full consolidation of a bioenergy industry is currently challenged by a sufficient, resilient, and resource-efficient biomass supply and an effective conversion process. Here, we provide a comprehensive analysis of how stable isotope approaches have accelerated the development of a robust bioeconomy by advancing knowledge about environmental sustainability, feedstock development, and biological conversion. We show that advances in stable isotope research have generated crucial information to (1) gain mechanistic insight into the potential of bioenergy crops to mitigate climate change as well as their impact on water and nutrient cycling; (2) develop high-yielding, resilient feedstocks that produce high-value bioproducts in planta; and (3) engineer microbes to enhance feedstock conversion to bioenergy products. Further, we highlight knowledge gaps that could benefit from future research facilitated by stable isotope approaches. We conclude that advances in mechanistic knowledge and innovations within the field of stable isotopes in cross-disciplinary research actions will greatly contribute to breaking down the barriers to establishing a robust bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A systems-level analysis of drought and density response in the model C4 grass Setaria viridis

The need for novel crops in an emerging bioenergy economy presents many challenges and opportunities for plant scientists. Plant breeding has been successful at transforming weedy species into some of the highest yielding crops on the planet. The plant domestication has led, in part, to an anticipated delivery of up to 1 billion dry tons of lignocellulosic feedstocks into the energy economy by 2030. However, The success of modern food crop breeding suggests that even greater advances can be made by developing the next generation of bioenergy feedstocks from C4 grass species that have been to date subjected to little or no breeding. The challenge we face is to exponentially accelerate the crop improvement process so that we can meet this level of bioenergy feedstock production. To achieve this unprecedented goal, it will be necessary to rapidly advance the process of plant breeding through large-scale biology, computational biology and systems approaches. Therefore, the goal of this proposal was to understand how productivity, drought tolerance and water use efficiency (WUE) are regulated at the genomic level in order to inform metabolic engineering and molecular-assisted breeding efforts.This necessitates the use of a model species that is closely related to less genetically tractable feedstock grasses such as Sorghum, switchgrass and Miscanthus. To achieve this we have significantly enhanced the utility of Setaria viridis as a model C4 species for system biology. This was achieved through field, greenhouse and laboratory experiments to survey a breadth of environments and explore the potential of gene networks to predict physiological responses across environments. We challenged plants under abiotic stresses to examine the plasticity of the network and identify targets for future manipulation. Finally, we have identified promising new gene engineering technologies to modify genetic networks in this model C4 species to understand and enhance abiotic stress tolerance. The outcomes of this project led to 1) identification of gene regulatory and metabolic networks important for adaptation to low water availability and high-density plantings, which lead to a greater understanding of the physiology underlying these adaptations and 2) we developed technologies to measure important water use efficiency traits and to precisely control gene insertion and replacements events for large scale engineering of pathways in model and target feedstocks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Quantum Computing for Quantum Simulation for NNSA Mission

Beginning with Feynman in 1982, it was proposed that highly controllable quantum devices, later to become known as quantum computers, would be especially good at the simulation of other quantum systems. Around the turn of the 21st century, this notion was later formalized (by Lloyd and coworkers at MIT and Laflamme and coworkers at Los Alamos) to show how in particular instances, we expect an exponential speedup in the solution of the Schroedinger equation for chemical systems. Subsequently, quantum-accelerated quantum simulation for chemistry techniques have been developed by IBM, Google, Harvard, etc. This effort has led to the OpenFermion (openfermion.org, OF) community, an open source effort for compiling and analyzing quantum algorithms to simulate fermionic systems, including quantum chemistry. Among other functionalities, the current version of OF features data structures and tools for obtaining and manipulating representations of fermionic and qubit Hamiltonians. In October, 2017, the cover of Chemical and Engineering News posited “Quantum computers: Chemistry could be the machine’s killer app” for first principles understanding of biological systems and complex materials. Prof. Aspuru-Guzik (Harvard) predicts “I think that before 2035 QC will be beating classical computers at chemistry.” The algorithms at the heart of quantum chemistry codes (eigensolvers, fast fourier transforms) are the computation bottleneck.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Accelerometer Modeling in the State-Space

Generically, accelerometers are sensors that measure the accelerating force applied to an object. Their operation is based on a simple mechanical system and D’Alembert’s force principle along with Newton’s laws of motion. This device is typically mounted to the body of the test object under investigation that is subjected to an accelerating force. The displacement of the seismic or “proof” mass due to the acceleration is sensed by an embedded component from which the acceleration is determined. Interestingly enough, the resulting the resulting mathematical relations governing the dynamical motion is based on the underlying physics, sensor materials, geometry and fabrication. Mathematically, the various designs satisfy the underlying Newtonian equations of motion, but their type and performance differ significantly.

42 ENGINEERING↗
DOE OSTI2015

Procter & Gamble Wind and Solar Analysis Summary

This LETTER REPORT has been prepared by Idaho National Laboratory (INL) as a basic summary of wind data, solar data, and energy production analyses for the Procter & Gamble (P&G) Box Elder Plant in Tremonton, UT. Along with this initial analysis report, future development studies/reports may go into more detail and be used to support the development of a renewable energy projects on P&G property. These summaries may also be used as supplemental material to support and accelerate further data analysis by other parties involved in the final development and construction of a renewable project.

14 SOLAR ENERGY↗
DOE OSTI2026

Multitarget Rydberg gates via spatial blockade engineering

Multi-target gates offer the potential to reduce gate depth in syndrome extraction for quantum error correction. Although neutral-atom quantum computers have demonstrated native multi-qubit gates, existing approaches that avoid additional control or multiple atomic species have been limited to single-target gates. We propose single-control-multi-target CZ^n gates on a single-species neutral-atom platform that require no extra control and have gate durations comparable to standard CZ gates. Our approach leverages tailored interatomic distances to create an asymmetric blockade between the control and target atoms. Using a GPU-accelerated pulse synthesis protocol, we design smooth control pulses for CZZ and CZZZ gates, achieving fidelities of up to 99.55% and $99.24\%$, respectively, even in the presence of simulated atom placement errors and Rydberg-state decay. Our approach is most effective for N=2 (CZZ) and N=3 targets (CZZZ); for larger N, increasing spatial crowding of the targets introduces significant challenges for maintaining the required blockade asymmetry. This work presents a practical path to implementing low-overhead multi-target gates in single-species neutral-atom systems, significantly reducing the resource overhead for syndrome extraction. To motivate the impact of these gates, we apply a greedy scheduling algorithm and we demonstrate that our proposed gates can reduce the number of atom reconfiguration costs by up to 50% for color code syndrome extraction of code distances greater than 5.

Stein, Samuel A.↗
DOE OSTI2019

Lightwave-driven gapless superconductivity and forbidden quantum beats by terahertz symmetry breaking

Light-induced supercurrents chart a path forward for the electromagnetic design of emergent materials phases and collective modes for quantum engineering applications. However, controlled spatial–temporal modulation of the complex order parameter characterizing such non-equilibrium macroscopic quantum states remains elusive. Such ultrafast phase-amplitude modulation can manifest via high harmonic modes beyond those allowed by equilibrium symmetries. Here, we drive moving condensate states via subcycle dynamical symmetry breaking achieved with nonlinear oscillating terahertz photocurrents. These non-equilibrium macroscopic quantum states with broken inversion symmetry are controlled via Cooper pair acceleration by asymmetric and multi-cycle terahertz photoexcitations. Furthermore, the observed supercurrent-carrying states evolve during a lightwave cycle and exhibit three distinguishing features: Anderson pseudo-spin precessions forbidden by equilibrium symmetry, strong high harmonic coherent oscillations assisted by pairing and long-lived gapless superfluidity with minimal condensate quench. Lightwave tuning of persistent photocurrents can be extended for quantum control of unconventional superconductors and topological matter, with implications on quantum gate and sensing functionalities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

On the synthesis of heavy nuclei in protomagnetar outflows and implications for ultra-high energy cosmic rays

ABSTRACT It has been suggested that strongly magnetized and rapidly rotating protoneutron stars (PNSs) may produce long duration gamma-ray bursts (GRBs) originating from stellar core collapse. We explore the steady-state properties and heavy element nucleosynthesis in neutrino-driven winds from such PNSs whose magnetic axis is generally misaligned with the axis of rotation. We consider a wide variety of central engine properties such as surface dipole field strength, initial rotation period, and magnetic obliquity to show that heavy element nuclei can be synthesized in the radially expanding wind. This process is facilitated provided the outflow is Poynting-flux dominated such that its low entropy and fast expansion time-scale enables heavy nuclei to form in a more efficient manner as compared to the equivalent thermal GRB outflows. We also examine the acceleration and survival of these heavy nuclei and show that they can reach sufficiently high energies ≳ 1020 eV within the same physical regions that are also responsible for powering gamma-ray emission, primarily through magnetic dissipation processes. Although these magnetized outflows generally fail to achieve the production of elements heavier than lanthanides for our explored electron fraction range 0.4–0.6, we show that they are more than capable of synthesizing nuclei near and beyond iron peak elements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Recovery Act: Oxy-Combustion Technology Development for Industrial-Scale Boiler Applications

Alstom Power Inc. (Alstom), under U.S. DOE/NETL Cooperative Agreement No. DE-NT0005290, is conducting a development program to generate detailed technical information needed for application of oxy-combustion technology. The program is designed to provide the necessary information and understanding for the next step of large-scale commercial demonstration of oxy combustion in tangentially fired boilers and to accelerate the commercialization of this technology. The main project objectives include: • Design and develop an innovative oxyfuel system for existing tangentially-fired boiler units that minimizes overall capital investment and operating costs. • Evaluate performance of oxyfuel tangentially fired boiler systems in pilot scale tests at Alstom’s 15 MWth tangentially fired Boiler Simulation Facility (BSF). • Address technical gaps for the design of oxyfuel commercial utility boilers by focused testing and improvement of engineering and simulation tools. • Develop the design, performance and costs for a demonstration scale oxyfuel boiler and auxiliary systems. • Develop the design and costs for both industrial and utility commercial scale reference oxyfuel boilers and auxiliary systems that are optimized for overall plant performance and cost. • Define key design considerations and develop general guidelines for application of results to utility and different industrial applications. The project was initiated in October 2008 and the scope extended in 2010 under an ARRA award. The project completion date was April 30, 2014. Central to the project is 15 MWth testing in the BSF, which provided in-depth understanding of oxy-combustion under boiler conditions, detailed data for improvement of design tools, and key information for application to commercial scale oxy-fired boiler design. Eight comprehensive 15 MWth oxy-fired test campaigns were performed with different coals, providing detailed data on combustion, emissions, and thermal behavior over a matrix of fuels, oxyprocess variables and boiler design parameters. Significant improvement of CFD modeling tools and validation against 15 MWth experimental data has been completed. Oxy-boiler demonstration and large reference designs have been developed, supported with the information and knowledge gained from the 15 MWth testing. The results from the 15 MWth testing in the BSF and complimentary bench-scale testing are addressed in this volume (Volume II) of the final report. The results of the modeling efforts (Volume III) and the oxy boiler design efforts (Volume IV) are reported in separate volumes.

42 ENGINEERING↗
DOE OSTI2021

Cyberbiosecurity and Public Health in the Age of COVID-19

Cyberbiosecurity, the aspect of biosecurity involving the digital representation of biological data, had already been emerging as a matter of public concern even prior to the onset of the COVID-19 pandemic. Key issues of concern include, among others, the privacy of patient data, the security of public health databases, the integrity of diagnostic test data, the integrity of public biological databases, the security implications of automated laboratory systems and the security of proprietary biological engineering advances. With the onset of the COVID-19 pandemic, and the importance of digital resources in combatting it, concern about the potential for cyber attacks by state-based or non-state actors has been elevated. To illuminate the challenges, we focus on the cyber vulnerabilities that need to be addressed in public health activities such as disease surveillance and outbreak management. In particular, we examine cyber issues raised by the accelerated pace of development for COVID mitigations, treatments, and vaccines.

cybersecurity, biosecurity↗
DOE OSTI2024

Surrogate Model Guided Optimization of Expensive Black-Box Multi-Objective Problems: A Posteriori Methods

Many engineering applications require the simultaneous optimization of multiple conflicting objective functions. Often, these objective functions are evaluated using highly accurate computer simulations that are computationally too expensive to be evaluated hundreds or thousands of times during optimization. Thus, the goal is to find good approximations of the Pareto front using as few of these expensive simulations as possible. Here, we describe an optimization approach based on surrogate models and diverse sampling strategies to accelerate the search for the Pareto solutions. We use a separate surrogate model for approximating each objective function and then we use the surrogate models to inform where additional expensive simulations should be run. The surrogate models are updated in an active learning framework whenever new information from the expensive simulations becomes available. The sampling strategies aim at balancing local improvements of the approximate Pareto front and global exploration to identify the extrema and fill in large gaps of the approximate Pareto front. We demonstrate on a large set of benchmark problems the effectiveness of the method for finding good approximations of the Pareto front.

MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Deciphering flux adjustments of engineered E. coli cells during fermentation with changing growth conditions

Microbial fermentation conditions are dynamic, due to transcriptional induction, nutrient consumption, or changes to incubation conditions. In this paper, 13 C-metabolic flux analysis was used to characterize two violacein-producing E. coli strains with vastly different productivities, and to profile their metabolic adjustments resulting from external perturbations during fermentation. The two strains were first grown at 37 °C in stage 1, and then the temperature was transitioned to 20 °C in stage 2 for the optimal expression of the violacein synthesis pathway. After induction, violacein production was minimal in stage 3, but accelerated in stage 4 (early production phase) and 5 (late production phase) in the high producing strain, reaching a final concentration of 1.5 mmol/L. On the contrary, ~0.02 mmol/L of violacein was obtained from the low producing strain. To have a snapshot of the temporal metabolic changes in each stage, we performed 13 C-MFA via isotopomer analysis of fast-turnover free metabolites. The results indicate strikingly stable flux ratios in the central metabolism throughout the early growth stages. In the late stages, however, the high producer rewired its flux distribution significantly, which featured an upregulated pentose phosphate pathway and TCA cycle, reflux from acetate utilization, negligible anabolic fluxes, and elevated maintenance loss, to compensate for nutrient depletion and drainage of some building blocks due to violacein overproduction. The low producer with stronger promoters shifted its relative fluxes in stage 5 by enhancing the flux through the TCA cycle and acetate overflow, while exhibiting a reduced biomass growth and a minimal flux towards violacein synthesis. Finally, interestingly, the addition of the violacein precursor (tryptophan) in the medium inhibited high producer but enhanced low producer's productivity, leading to hypotheses of unknown pathway regulations (such as metabolite channeling).

13C-MFA↗
DOE OSTI2026

Surrogates for Valve-Controlled Pipe Flow: Accelerating Nuclear Reactor Design

Neural surrogate models are developed to replace expensive steady-state RANS CFD simulations for valve-controlled pipe flow in nuclear reactor design. Using parametric CFD data generated with MOOSE Pronghorn across a range of valve geometry and flow conditions, three approaches are compared: a POD-based reduced-order model, a structured UNet on a cylindrical grid, and unstructured models (DeepONet and BiStride MeshGraphNet) on nondimensionalized point clouds. POD achieves the highest accuracy (99%) with fast inference but requires storing all solution snapshots, while the DeepONet and BSMS-GNN both achieve ~89% accuracy at sub-second inference, with the BSMS-GNN offering superior geometric generalizability. These surrogates enable rapid ranking of candidate valve designs and can warm-start CFD solvers to accelerate convergence, supporting agentic design iteration on the Prometheus platform.

42 - ENGINEERING↗
DOE OSTI2023

Optimal decision-making in high-throughput virtual screening pipelines

Screening large pools of molecular candidates to identify those with specific design criteria or targeted properties is demanding in various science and engineering domains. While a high-throughput virtual screening (HTVS) pipeline can provide efficient means to achieving this goal, its design and operation often rely on experts' intuition, potentially resulting in suboptimal performance. In this paper, we fill this critical gap by presenting a systematic framework that can maximize the return on computational investment (ROCI) of such HTVS campaigns. Based on various scenarios, we empirically validate the proposed framework and demonstrate its potential to accelerate scientific discoveries through optimal computational campaigns, especially in the context of virtual screening.

97 MATHEMATICS AND COMPUTING↗