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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Requirements Documents for the Large Mechanical Parts Precision Cleaner (LMPPC) in the Optics Assembly Building (OAB)

The National Ignition Facility (NIF) is the world's largest energetic laser whose missions include sresearch in inertial confinement fusion, experiments for the Stockpile Stewardship, and other high fluence laser research. Due to the high fluence of lasers, extreme environmental conditions, and radiation presence, all mechanical parts (metal, plastic, etc.) installed on NIF must be precision cleaned. Precision cleaned parts are also required in supporting facilities like the Optics Processing Facility (OPF). Small debris inside the laser beams or on optics can cause optic damage, interfere with diagnostics, and interfere with experiments.

42 ENGINEERING↗
DOE OSTI2023

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Industry 4.0 and Intelligent Manufacturing Processes: A Review of Modern Sensing Technologies

Digital Manufacturing technologies have quickly become ubiquitous in the manufacturing industry. The transformation commonly referred to as the fourth industrial revolution, or Industry 4.0, has ushered in a wide range of communication technologies, connection mechanisms, and data analysis capabilities. These technologies provide powerful tools to create a more lean, profitable, and data-driven manufacturing processes. In this paper, we review modern communication technologies and connection architectures for Digital Manufacturing and Industry 4.0 applications. An introduction to Cyber-Physical Systems and a review of digital manufacturing trends is followed by an overview of data acquisition methods for manufacturing processes. Numerous communication protocols are presented and discussed for connecting disparate machines and processes. Flexible data architectures are discussed and examples of machine monitoring implementations are provided. Finally, select implementations of these communication protocols and architectures are surveyed with recommendations for future architecture implementations.

42 ENGINEERING↗
DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
DOE OSTI2024

Ultra-High-Speed X-ray Tomography: Bridging the Gaps to See the Unknown

Rapid, time-varying, three-dimensional physics underpin numerous engineering challenges. Often, these physics occur within opaque environments, internal to a component, severely limiting applicable diagnostics. Development of novel diagnostics is necessary to understand and predict transient three-dimensional (3D) phenomena within opaque environments. This report highlights progress in four key areas leading to advancements in high-speed X-ray radiography and tomography. The first area is enabling MHz-rate imaging of energetics at the Advanced Photon Source at Argonne National Laboratory. The second is modeling a high-flux, rotating-anode X-ray source to understand the heat loads on the anode. The third effort was to develop a novel reconstruction algorithm that is validated by ground experimental tomography data and synthetic tomography data. The fourth is the development of a novel approach to two-color X-ray imaging.

42 ENGINEERING↗
DOE OSTI2022

CORRTEX Analysis Techniques

Continuous Reflectometry for Radius versus Time Experiments, or CORRTEX, is a diagnostic that was developed during nuclear testing to measure the distance at which rock walls were disrupted by an explosive device as a function of the time at which disruption occurred. Distances recorded are dynamic measurements of cable length as the shockwaves from an explosive event crush the experiment cables, reducing their usable length. Applications of the CORRTEX diagnostic have been expanded in recent times to include instrumentation of the explosive device itself, to record phenomena such as the speed of the detonation wave in the explosive charge and the crushing or disassembly of material in the charge housing. The diagnostic has likewise been used to monitor explosive performance in rock blasting and oil well hole-clearing activities.

42 ENGINEERING↗
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

High-Speed Diagnostic and Simulation Capabilities for Reacting Hypersonic Reentry Flows (LDRD Final Report)

High-enthalpy hypersonic flight represents an application space of significant concern within the current national-security landscape. The hypersonic environment is characterized by high-speed compressible fluid mechanics and complex reacting flow physics, which may present both thermal and chemical nonequilibrium effects. We report on the results of a three-year LDRD effort, funded by the Engineering Sciences Research Foundation (ESRF) investment area, which has been focused on the development and deployment of new high-speed thermochemical diagnostics capabilities for measurements in the high-enthalpy hypersonic environment posed by Sandia's free-piston shock tunnel. The project has additionally sponsored model development efforts, which have added thermal nonequilibrium modeling capabilities to Sandia codes for subsequent design of many of our shock-tunnel experiments. We have cultivated high-speed, chemically specific, laser-diagnostic approaches that are uniquely co-located with Sandia's high-enthalpy hypersonic test facilities. These tools include picosecond and nanosecond coherent anti-Stokes Raman scattering at 100-kHz rates for time-resolved thermometry, including thermal nonequilibrium conditions, and 100-kHz planar laser-induced fluorescence of nitric oxide for chemically specific imaging and velocimetry. Key results from this LDRD project have been documented in a number of journal submissions and conference proceedings, which are cited here. The body of this report is, therefore, concise and summarizes the key results of the project. The reader is directed toward these reference materials and appendices for more detailed discussions of the project results and findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Understanding asymmetries using integrated simulations of capsule implosions in low gas-fill hohlraums at the National Ignition Facility

Current capsule implosions at the National Ignition Facility (NIF) using high-density-carbon ablators and laser energies close to 2 MJ have shown neutron yields in excess of 50 kJ. Improving on this performance requires understanding of the different degradation mechanisms. For many NIF implosions, nuclear diagnostic signatures have inferred residual hot-spot velocities that correlate with fuel areal density variations consistent with a low-order mode-1 asymmetry. A current working hypothesis attributes these asymmetries to a combination of beam to beam variations in the laser delivery and possibly coupling to target features, such as the diagnostic holes needed for x-ray imaging. Recently, a new source has been identified, thickness variation in the ablator shell. To gain better understanding and eventually mitigate the causes of <ρR> asymmetries, 3D integrated simulations using the actual delivered laser powers are needed. To capture the effect of the diagnostic holes (DHs) using direct numerical simulation would require significantly large computational resources. Instead, our 3D simulations make use of a subgrid model developed using highly-resolved 2D simulations that include several details of the DH engineering complexity. Simulations of NIF shots using hohlraums without DHs, to isolate the effect of beam-to-beam variations, reproduce fairly well the observed nuclear diagnostic signatures. Similarly, reasonable agreement between data and simulations is also obtained in the presence of diagnostic holes. To account for the remaining discrepancies a sensitivity study of ablator thickness variation showed that 1% thickness asymmetries are comparable in effect to 1% peak drive mode-1 asymmetries. Furthermore, this study identified sensitivity to variations in the imbedded doped layer (needed to shield the DT ice from the high energy x-rays generated in the hohlraum) thickness even when the inner and outer surface of the ablator are perfectly spherical.

radiation hydrodynamics↗
DOE OSTI2022

Bulk Spray and Individual Plume Characterization of LPG and Iso-Octane Sprays at Engine-Like Conditions

This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models. Optical imaging revealed that unlike iso-octane, propane’s spray propagation was fed by its flash boiling, spray collapse, and high degree of vaporization, resulting in a direct proportionality of propane’s penetration length to temperature. These unique features of propane and its variation from iso-octane’s spray pattern, contributed to its classification as an unconventional spray. Appropriate corrections to the injection and breakup models were developed to reproduce the under-expanded jet dynamics and to mimic the flash boiling-driven spray development observed with propane sprays. The simulation results were found to be sensitive to cone and inclusion angles of the blob injector. The current work represents a first assessment of the capability of the commonly available models for engine-spray simulations and highlights the fact that, despite the reasonable agreement obtained in the fuel vapor morphology, the representation of the liquid phase lacks accuracy and requires further model development.

02 PETROLEUM↗
DOE OSTI2025

Pressure Gain, Stability, and Operability of Methane/Syngas Based RDEs Under Steady and Transient Conditions (Final Project Report)

The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.

08 HYDROGEN↗
DOE OSTI2024

Symbolic diagnostics to interpret and analyze neural network models

Embedded machine-learned models (EMLMs) have the promise to improve the predictive accuracy of engineering simulators in environments of national interest. EMLMs often comprise complex input-output maps (e.g., neural networks), which make them unamenable to rigorous analysis and generally difficult to interpret. In the face of decades of theory, this lack of interpretability is a significant barrier to building confidence in these models. This work outlines an approach to interpret EMLMs using sparse polynomial regression for comparison with theoretical understanding. To do so, we build on the concept of Locally Interpretable Model-agnostic Explanations (LIME) using physics-informed clustering, prototype selection, and library construction. While general, we demonstrate our method on tensor-basis neural networks used in Reynolds-Averaged Navier-Stokes simulations of hypersonic fluid flows. Results are presented for a simulated toy model and for direct numerical simulations (DNS) of turbulent flows over a flat plate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Diagnostic methods for a high efficiency exhaust aftertreatment system

A method includes interpreting NOx data indicative of an amount of NOx exiting an engine and an amount of NOx exiting an exhaust aftertreatment system coupled to the engine, determining a NOx conversion efficiency fault is present based on the amount of NOx exiting the engine and the amount of NOx exiting the exhaust aftertreatment system, and determining at least one of a selective catalytic reduction (SCR) catalyst of the exhaust aftertreatment system and a diesel particulate filter having a coating of a SCR reaction catalyst (DPF-SCR) of the exhaust aftertreatment system are responsible for the NOx conversion efficiency fault based on at least one of a reductant slip amount and a NOx conversion value across at least one of the SCR catalyst and the DPF-SCR.

42 ENGINEERING↗
DOE OSTI2022

On the Feasibility of Geophysical Methods for CO 2 Monitoring in the North Dakota CarbonSAFE Project

Conference presentation at American Institute of Chemical Engineers (AIChE) Annual Meeting, Phoenix, AZ, November 13–18, 2022. An analysis of rock physics crossplots and diagnostic models suggests that the baseline seismic data may be sensitive to changes in lithology and porosity of the Broom Creek Formation and that these changes may be detectable by prestack seismic inversion.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Fuel properties effects on wall-wetting and fuel-in-lube dilution under stochastic pre ignition prone conditions

Fuel-engine interactions have been shown to influence stochastic pre-ignition (SPI), however there is uncertainty on the root causes, participially if effects are primarily physical or chemical in nature. To better delineate the physical and chemical dependencies of fuel properties on SPI, this work studies interactions between aromatics, distillation, and particle matter index on SPI with a laser induced fluorescence (LIF) diagnostic to observe wall wetting. Fuels with high aromatic components or higher distillation temperatures tend to increase SPI events, but it is not well understood if the increased fuel dilution or a chemical aspect of this process is the primary mechanism for SPI. By employing the novel LIF in this work we measure fuel dilution in real-time in a running single cylinder research engine operated at SPI conditions. Three fuels were used in the present work, with the LIF diagnostic. Each fuel was operated at two injection timings, generating fuel specific effects on wall wetting. The LIF measurements are coupled with engine combustion measurements and SPI event counts. Results enable a deconvolution of fuel physical and chemical properties on SPI propensity, providing unique and novel insights into the dominant fuel effects affecting SPI.

Splitter, Derek↗