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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Detonator Design Guide and Knowledge Capture System [Slides]

Engineering design--good design--is a blend of engineering and science; this is especially true for of explosive detonator design. Detonators are complex components with interrelated mechanical, electrical, and chemical attributes, all of which must be balanced to achieve a robust and reliable, working whole. This design guide presents an integrated, lifecycle approach to the design process, bringing together engineering design with science, emphasizing elegance and subtlety in the design process.

42 ENGINEERING↗
DOE OSTI2023

WAVES [Slides]

WAVES (LANL code C23004) is a computational engineering workflow tool that integrates parametric studies with traditional software build systems.

42 ENGINEERING↗
DOE OSTI2023

R&D DC Electrical Safety [Slides]

Objectives: Recognize DC and pulsed electrical hazards; Improve risk assessment skills; Concepts to improve worker safety; Engineered vs. administrative controls; tools of the trade.

42 ENGINEERING↗
DOE OSTI2022

Editorial: Particulate Matter Emissions From Conventional and Reformulated Fuel Combustion: Advances in Experiments and Simulations

Particulate matter (PM or soot) emissions generated by combustion of conventional and reformulated fuels adversely impact the environment and human health (Bond et al., 2013; Landrigan et al., 2018; World Health Organization (WHO), 2016), generating public awareness and motivating efforts towards the mitigation of their harmful effects. Soot formation is one of the most complex phenomena in combustion, involving interactions between combustion chemistry, fluid mechanics, mass/heat transport, and particle dynamics, spanning different spatial and temporal scales. A fundamental understanding of soot formation process is thus necessary to achieve a strong reduction of PM emissions and design cleaner and more efficient combustion systems. This has motivated a longstanding and ongoing research activity aimed at improving our understanding of the physical and chemical processes involved in soot formation, well reviewed in these recent works (Wang and Chung, 2019; Michelsen et al., 2020; Martin et al., 2022). Despite the wide interest, the transition from gas-phase molecules to incipient soot particles is still elusive and the successive particle growth and oxidation processes are far from being fully understood, especially in conditions relevant to real-world applications. Recent advances in combustion PM emission diagnostic and computational capabilities helped in improving the predictability of fundamental chemical and aerosol models for practical applications, thus tackling some of the above-mentioned challenges. The aim of this research topic is to display the ongoing research efforts in addressing the existing gaps on particulate formation from various fuel sources and in conditions typical of practical combustion applications (e.g. flames, engines, pool fires), through both experimental and numerical approaches.

42 ENGINEERING↗
DOE OSTI2020

Identification of Promising Alternative Mono-Alcohol Fuel Blend Components for Spark Ignition Engines

Alcohols are attractive fuel blendstocks for spark ignition engines due to their high octane values and potentially positive influence on performance and emission. Although methanol, ethanol, and butanol have been widely studied, other biomass-derived alcohols may have similar or better properties. However, it is not feasible to experimentally investigate the fuel potential of every molecule. The goals of this study were to develop a methodology for rapid screening of a fuel property database for mono-alcohols and to identify alcohols with the potential of blending to produce advantaged motor gasolines. A database was developed with 13 fuel properties of all saturated C1–C10 mono-alcohols. A decision framework was used to evaluate alcohols suitable for blending in gasoline for spark ignition engines in two scenarios: low-range (up to 15 vol%) blends and high-range (greater than 40 vol%) blends. The low-range blend cases resulted in the identification of 48 alcohols. In the case of high-range blending, only six alcohols were found to be suitable. This is the first study to systematically evaluate all C1–C10 saturated alcohols for blending with gasoline using relevant fuel properties. A novel aspect of this study is the evaluation of the influence of errors in predicted property values. These scenario screenings focus attention on a smaller number of promising candidate molecules, and the approach could be modified for other classes of fuel molecules, engine types, and fuel blending goals.

42 ENGINEERING↗
DOE OSTI2021

CCE and Resilience Strategies

Consequence-driven Cyber-informed Engineering (CCE) is a methodology focused on securing the nation’s critical infrastructure systems. Developed at Idaho National Laboratory, CCE starts with the assumption that if a critical infrastructure system is targeted by a skilled and determined adversary, the targeted network can and will be penetrated. This think like the adversary approach provides critical infrastructure owners, operators, vendors and manufacturers with a disciplined methodology to: evaluate complex systems; determine what must be fully safeguarded; and apply proven engineering strategies to isolate and protect an industry’s most critical assets.

42 ENGINEERING↗
DOE OSTI2024

Geomembranes for Pumped Storage Hydro

Energy storage is fundamental to ensuring the reliability, stability, and resilience of the grid, essential for meeting the energy demands now and in the future. Pumped storage stands out as a proven energy storage solution. There are 43 pumped-storage plants operating in the USA today, and they offer unparalleled scalability, rapid-response capabilities, and long-term reliability at a competitive cost. With a history of successful operation spanning decades, and approximately 60 sites proposed at various stages of permitting and development, this technology is a critical component for the US energy sector. However, its development involves some complex engineering and regulatory challenges.

13 HYDRO ENERGY↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2022

Conversion of Phenolic Oil from Biomass Pyrolysis into Phenyl Esters

Bio-oil is among the most economical approaches for advanced biofuel production. However, bio-oil faces several challenges including high acidity and viscosity, poor storage, and thermal stability. This study focuses on the upgradation of lignocellulosic (corn stover and yellow pine) bio-oil derived phenolic oil (PO), produced by the autothermal fast pyrolysis, through acid-catalyzed esterification reaction. Our strategy exploits a little recognized chemistry: the Fischer esterification of PO and carboxylic acids into carboxylic acid phenyl esters (CAPE) using Dean Stark distillation. Analyses by the Folin–Ciocalteu method, Karl Fischer titration, gas chromatography flame ionization detector, and the molecular weight determination by gel permeation chromatography suggest the conversion of 50 wt% added phenolics to their corresponding CAPE. The Fourier transform infrared spectroscopy analysis confirmed the formation of new C=O and two C–O stretching bands and decrease in the intensity of phenolic-OH bands in the CAPE. The 13 C NMR analysis supports the formation of CAPE together with some unreacted precursors. A base-catalyzed ester hydrolysis experiment and mass balance calculation show an excellent agreement (within 5% range) of the equivalent weight between the produced ester and the phenyl hexanoate. Brookfield analysis indicates that CAPE has 330-fold lower viscosity than starting PO. Heating values of CAPE were higher than PO, from which they were derived (42.2 and 43.6%, respectively, for PO from pyrolysis of corn stover and yellow pine), while moisture content decreased by 98.3 and 98.7%, respectively. The CAPE, which is a phenolic analogue of methyl esters used in biodiesel, has improved stability compared to PO from which it was derived.

42 ENGINEERING↗
DOE OSTI2020

Efficient Generalized Boundary Detection Using a Sliding Information Distance

In this work, we present a general machine learning algorithm for boundary detection within general signals based on an efficient, accurate, and robust approximation of the universal normalized information distance. Our approach uses an adaptive sliding information distance (SLID) combined with a wavelet-based approach for peak identification to locate the boundaries. Special emphasis is placed on developing an adaptive formulation of SLID to handle general signals with multiple unknown and/or drifting section lengths. Although specialized algorithms may outperform SLID when domain knowledge is available, these algorithms are limited to specific applications and do not generalize. SLID excels in these cases. We demonstrate the versatility and efficacy of SLID on a variety of signal types, including synthetically generated sequences of tokens, binary executables for reverse engineering applications, and time series of seismic events.

42 ENGINEERING↗
DOE OSTI2021

Comparison of Polymer AM Technologies for Automotive Tooling for Composite Engines

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with Polimotor to complete a set of molds for fabricating the oil pan for a composite engine. This project used multiple different AM processes to fabricate the mold set. The assembled parts were measured for tolerance and then sent to Polimotor to be used in the manufacture of engine components.

42 ENGINEERING↗
DOE OSTI2021

Review of Release Behavior of Hydrogen & Natural Gas Blends from Pipelines

Hydrogen can be used to reduce carbon emissions by blending into other gaseous energy carriers, such as natural gas. However, hydrogen blending into natural gas has important implications for safety which need to be evaluated. Hydrogen has different physical properties than natural gas, and these properties affect safety evaluations concerning a leak of the blended gas. The intent of this report is to begin to investigate the safety implications of blending hydrogen into the natural gas infrastructure with respect to a leak event from a pipeline. A literature review was conducted to identify existing data that will better inform future hazard and risk assessments for hydrogen/natural gas blends. Metrics with safety implications such as heat flux and dispersion behavior may be affected by the overall blend ratio of the mixture. Of the literature reviewed, there was no directly observed separation of the hydrogen from the natural gas or methane blend. No literature was identified that experimentally examined unconfined releases such as concentration fields or concentration at specific distances. Computational efforts have predicted concentration fields by modified versions of existing engineering models, but the validation of these models is limited by the unavailability of literature data. There are multiple literature sources that measured flame lengths and heat flux values, which are both relevant metrics to risk and hazard assessments. These data can be more directly compared to the outputs of existing engineering models for validation.

03 NATURAL GAS↗
DOE OSTI2022

Physically rigorous reduced-order flow models of fractured subsurface environments without explosive computational cost

Fractured media models comprise discontinuities of multiple lengths (e.g. fracture lengths and apertures, wellbore area) that fall into the relatively insignificant length scales spanning millimeter-scale fractures to centimeter-scale wellbores in comparison to the extensions of the field of interest, and challenge the conventional discretization methods imposing highly-fine meshing and formidably large numerical cost. By utilizing the recent developments in the finite element analysis of electromagnetics that allow to represent material properties on a hierarchical geometry, this project develops computational capabilities to model fluid flow, heat conduction, transport and induced polarization in large-scale geologic environments that possess geometrically-complex fractures and man-made infrastructures without explosive computational cost. The computational efficiency and robustness of this multi-physics modeling tool are demonstrated by considering various highly-realistic complex geologic environments that are common in many energy and national security related engineering problems.

42 ENGINEERING↗