Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “repeatability”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparative Analysis of Imaging and Measurements of Micrometer-Scale Fracture Aperture Fields Within a Heterogeneous Rock Using PET and X-ray CT

Knowledge of the spatial distribution of fracture apertures is essential for reliable characterization of flow and transport processes in fractured systems and for better understanding of physicochemical matrix–fracture interactions. Here, we propose and test two image-based methods, thereby extending the current experimental capabilities to characterize aperture size distribution in structurally heterogeneous geologic porous media noninvasively. The first approach utilizes an inversion method based on the dataset acquired from positron emission tomography (PET) and the second approach considers an extension of the classic missing attenuation technique that relies on clinical X-ray computed tomography (X-ray CT). Independent sets of imaging experiments are conducted on a fractured basalt core with heterogeneous matrix properties and aperture distributions to compare the two methodologies. A repeat of each experiment is conducted to verify the proposed workflows. The performance of these two imaging techniques is systematically evaluated through the analysis of signal-to-noise ratio, minimum fracture size detectability, and measurement errors. While both approaches provide a reliable estimation of fracture aperture distributions, PET yields a signal-to-noise ratio that is substantially higher than the corresponding X-ray CT measurements. Furthermore, uncertainties of the aperture values for PET are considerably lower ($\bar {\sigma}_{\text {d}} = 15\%$) compared to those obtained from X-ray CT ($\bar {\sigma}_{\text {d}} = 29\%$), allowing for the detection of minimum aperture sizes of 20 $\mu$m with 70% confidence level. Finally, these approaches provide key experimental tools for better understanding dynamic hydromechanical fracture properties in geologic systems.

58 GEOSCIENCES↗
DOE OSTI2022

Interlaboratory Reproducibility of Contour Method Data in a High Strength Aluminum Alloy

The contour method for residual stress measurement has seen significant development, but an experimental reproducibility study utilizing physical samples has not been published. A double-blind reproducibly study is reported, having scope beginning with EDM cutting and ending with residual stress calculation. A reinforced I-beam sample geometry is identified for its unique residual stress profile when extracted from residual stress bearing quenched aluminum bar (7050-T74). Contour measurements are prescribed on a midplane of symmetry with dimensions 24.0 mm by 50.0 mm. Fourteen identically prepared samples are fabricated from a single long bar with well characterized and uniform residual stress. Five samples throughout the bar are identified for planning measurements to validate sample uniformity and overall suitability of the residual stress field. The planning measurements employ a range of techniques: contour method, neutron diffraction, and hole-drilling. Eight samples are distributed to an international group of participants to execute their standard measurement practice. A double-blind process is followed to provide anonymity. Results are provided by eight participants: six being self-similar and two being quite different, the latter set aside as outliers. An average residual stress field is established from non-outlying results and the spatial distribution of reproducibility standard deviation is determined. The average stress field ranges from -60 to 70 MPa and the reproducibility standard deviation averages 8.1 MPa on the measurement plane. The average reproducibility standard deviation is about 3 × larger for points within 1.0 mm of plane boundaries (17.6 MPa) than for the remaining points (6.1 MPa). Reproducibility standard deviation (among different labs) for contour method residual stress measurement is found to be very similar to repeatability standard deviation (in a single lab) reported in prior work. The reproducibility observed here, for the entire measurement process, is also similar to that found in a prior reproducibility study limited to contour method data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Full-Field Strain Measurement Integrated with Two Dimension Regression Analysis to Evaluate the Bi-Modulus Elastic Properties of Isotropic and Transversely Isotropic Materials

Background: Measuring the physical properties of shale is critical for optimizing engineering activities such as geothermal energy generation and hydraulic fracturing. Shale is a transversely isotropic material. Furthermore, this material can also include micro and macro cracks at different locations and orientations that cause it to behave differently under tensile or compressive loading. Objective: In this work, a combined experimental–numerical approach is proposed to evaluate the bi-modulus elastic properties of isotropic and transversely isotropic materials. Methods: Full-field strain measurements for a circular disk under diametral compression are integrated with a regression analysis technique to evaluate the elastic properties of bi-modulus materials subjected to tensile and compressive loads using two loading configurations on the same specimen. Digital Image Correlation (DIC) is used to measure the full-field strains. Subsequently, in the case of an isotropic material, a linear least-squares approach is utilized to process the experimentally determined strains in conjunction with analytical expressions of the stress fields (in terms of far-field loading) to determine the elastic modulus E, the shear modulus G, and the Poisson’s ratio $v$. In the case of a transversely isotopic material, such as shale, a finite element model is implemented to determine the stress fields (again in terms of far-field loading), which is followed by repeating the previous regression analysis in an iterative process to estimate the elastic parameters. Results: The results show that the proposed technique successfully provides a complete set of elastic properties as a function of both the loading condition and the principal material directions. The technique is validated by measurements on a known isotropic material and then applied to determine the properties of shale. Conclusion: In this work, the proposed approach is successfully used to calculate the bi-modulus elastic response of poly(methyl meth- acrylate) (PMMA) and shale. As expected, PMMA exhibits an isotropic response with no bi-modulus effect, however, shale exhibits both transverse isotropy and a bi-modulus effect. Therefore, this approach holds promise for investigating the elastic properties of materials like rocks and fiber-reinforced composite laminates as functions of the principal material directions and the loading conditions.

42 ENGINEERING↗
DOE OSTI2020

Long Term Creep Behavior of a CoCrFeNiMn High Entropy Alloy

The potential of high entropy alloys (HEAs) to meet or exceed austenitic stainless-steel performance with the additional benefit of improved hot corrosion/oxidation resistance makes FCC HEAs attractive for use in energy applications. While shorter term creep tests have been reported in the literature on HEAs, not all methodologies utilize repeatable techniques. This manuscript reports on over 23,500 accumulated hours of tensile creep testing with adherence to ASTM standards on a melt solidified ingot of CoCrFeNiMn HEA converted to wrought plate using conventional thermo-mechanical processing techniques. The typical standard creep analyses are reported, i.e., Larson-Miller parameter, Monkman-Grant relationship, activation energy for creep, and creep stress exponents were calculated and compared to previously reported short-term creep tests. Additionally, characteristics of creep fracture and microstructural evolution are reported with cursory dislocation mechanisms investigated.

Rozman, Kyle A.↗
DOE OSTI2025

Creep Behavior of Friction Stir Processed Haynes 282

Haynes 282 is a nickel-based superalloy designed for use in hot sections of turbines for aircraft and power generation. In these applications, elevated temperature creep performance is critical. To that end, creep behavior of friction stir processed material was carried out to investigate the high-temperature performance of this alloy. Friction stir processing of Haynes 282 was successfully completed, and the processed region was found to be defect-free. Various mechanical property characterization approaches were carried out in post-heat treated condition. Transverse tensile samples repeatedly failed in the base metal indicating 100% joint efficiency. Creep property evaluation was completed at 760 °C and at various stress levels. The creep-rupture lifetime of the processed material was similar to the base metal. Detailed electron microscopy analysis of the failed sample was carried out to understand the microstructural evolution in various locations of the sample during creep.

creep↗
DOE OSTI2022

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗
DOE OSTI2023

Investigation of Raster Pattern Spacing and Direction for Friction Stir Additive Manufacturing of Al-5083

Friction stir additive manufacturing (FSAM) is a sheet-lamination based additive manufacturing technique. In addition to the traditional factors that govern the friction stir process-structure-property relationship, the processing history is convoluted by the in-plane raster pattern and repeated thermal cycling from subsequent layers. This can lead to complex thermal gradients within the workpiece and reprocessing of material. Here, this work aims to understand the impact of raster pattern spacing and direction on the microstructure and properties during friction stir additive manufacturing of Al-5083. Control of the raster spacing can lead to an increase in hardness of up to 18% from the base material and defect-free joining. These results are then directly demonstrated at the component-scale for FSAM of Al-5083.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cross-national analysis of food security drivers: comparing results based on the Food Insecurity Experience Scale and Global Food Security Index

Abstract The second UN Sustainable Development Goal establishes food security as a priority for governments, multilateral organizations, and NGOs. These institutions track national-level food security performance with an array of metrics and weigh intervention options considering the leverage of many possible drivers. We studied the relationships between several candidate drivers and two response variables based on prominent measures of national food security: the 2019 Global Food Security Index (GFSI) and the Food Insecurity Experience Scale’s (FIES) estimate of the percentage of a nation’s population experiencing food security or mild food insecurity (FI ). We compared the contributions of explanatory variables in regressions predicting both response variables, and we further tested the stability of our results to changes in explanatory variable selection and in the countries included in regression model training and testing. At the cross-national level, the quantity and quality of a nation’s agricultural land were not predictive of either food security metric. We found mixed evidence that per-capita cereal production, per-hectare cereal yield, an aggregate governance metric, logistics performance, and extent of paid employment work were predictive of national food security. Household spending as measured by per-capita final consumption expenditure (HFCE) was consistently the strongest driver among those studied, alone explaining a median of 92% and 70% of variation (based on out-of-sample R 2 ) in GFSI and FI , respectively. The relative strength of HFCE as a predictor was observed for both response variables and was independent of the countries used for model training, the transformations applied to the explanatory variables prior to model training, and the variable selection technique used to specify multivariate regressions. The results of this cross-national analysis reinforce previous research supportive of a causal mechanism where, in the absence of exceptional local factors, an increase in income drives increase in food security. However, the strength of this effect varies depending on the countries included in regression model fitting. We demonstrate that using multiple response metrics, repeated random sampling of input data, and iterative variable selection facilitates a convergence of evidence approach to analyzing food security drivers.

42 ENGINEERING↗
DOE OSTI2025

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗
DOE OSTI2023

Balancing Impedance and Controllability in Response Reconstruction with $\mathrm{TS-IMMAT}$

In a prior work the authors proposed a variant on the Impedance Matched Multi-Axis Test (IMMAT) in which a fixture is defined, called the Transmission Simulator (TS), and the desired environment is matched at a set of sensors on the TS. If the motion of the TS is matched then the response of the rest of the component will also match, provided that the attached component has the same dynamics as it did when the environment was measured. Hence, one would like the TS to be flexible so that it reproduces the boundary conditions that the component of interest experiences during flight, but the more flexible the TS, the more shakers might be needed to control its response. This work presents a derivation that gives expressions for these two potential error sources in TS-IMMAT. Then, various case studies are presented, both on simulated and real hardware, to understand the importance of each error term in practical testing. The theory explains the phenomena that were observed when using measurements from a component that flew on a sounding rocket. The environmental response was measured and then various fixtures were attached, each comprising more of the next assembly, or the hardware to which the component was attached in flight. MIMO testing was repeated with each fixture and the results were compared to seek to understand the role of the impedance match in this type of testing. Here the results show that the number of modes that are active in the transmission simulator is also very important, and so the best solution balances these two considerations. An improved method of simulating the MIMO test is then proposed, so simulations can be used to predict what fixture, or transmission simulator, will give the best results in a TS-IMMAT test.

42 ENGINEERING↗
DOE OSTI2025

An Analysis of Input Parameters for Film-Based Flash X-Ray Radiography

Flash X-ray radiography (flash) is a commonly used diagnostic technique in dynamic experiments. An analysis of the effects of input parameters on resulting metrics of image quality can aid the experimentalist in configuring the X-ray input parameters to produce the highest quality radiograph for a given experiment. Here, a flash X-ray test bed with HS800 film and a LANEX Medium F intensifier screen was used with an L3 450 kVp pulser and Scandiflash X-ray tube for this study. Input parameters including charge voltage, source filtering, and film-pack assembly were investigated for their impact on contrast-to-noise ratio (CNR), contrast, and contrast transfer function (CTF). Using VIDAR’s NDT Pro industrial film digitizer, scanner parameters such as optical density range, pixel spacing, scan mode, and digital bit-depth were also examined for their impact on image quality metrics. The highest CNR values were found with two LANEX intensifiers and no filtering. Charge voltage had no direct impact on CNR values. LANEX screen count and filtering resulted both in direct effects on CNR and interaction effects with each other and CNR value. Uncertainty bounds for CNR comparisons and repeatability of CTF evaluations are also discussed. Finally, the film results are compared with a previous study using other detector types, specifically Carestream INDUSTREX Flex GP, Flex HR, Flex XL Blue, and HPX-DR 3543.

dynamic radiography↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
DOE OSTI2021

Projected Changes in Temperature and Precipitation Over the United States, Central America, and the Caribbean in CMIP6 GCMs

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between – 0.93 and 1.27 °C and – 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-first century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no significant difference was found, suggesting that model bias is not strongly influencing the projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Chapter 7 - CRISPR-Based Tools for Microbial Cell Factories

The development of microbial chassis for the production of a variety of biochemicals and biofuels is a growing area of research. How to efficiently manipulate genetic information to achieve optimal production of these compounds is a key area of focus in the field. In recent years, clustered regularly interspaced palindromic repeats (CRISPR) and its associated proteins (Cas) have become a popular strategy for gene editing and regulation in many organisms due to its versatility and efficacy. Here, we describe methods developed utilizing CRISPR-Cas systems for engineering microbial cell factories (e.g., bacteria and yeast) at the single gene to genome scale for mutagenesis and transcriptional regulation of target genes. Finally, we provide a perspective on the challenges and opportunities for the applications of advanced CRISPR-Cas-based tools for engineering microbial cell factories.

BIOMASS FUELS↗
DOE OSTI2022

Chapter 10: Advances in Protein Engineering and its Application in Synthetic Biology

Protein engineering has been used successfully in fields ranging from medicine to food science to biofuels. Applications of protein engineering include developing antiviral peptides or other protein therapeutics, antibody engineering, designing protein-based logic circuits, engineering enzymes to be more specific or to function under industrially relevant conditions such as at higher temperatures or high/low pH, modifying cell signaling or regulatory functions, and so on. Advances in recombinant DNA, "omics," and CRISPR-Cas (clustered regularly interspaced short palindromic repeats and its associated proteins) technologies, combined with high-throughput screening facilities, will lead to improved methods for protein engineering, enabling easy modification of more proteins/enzymes for new specific applications. New methods for rational design, directed evolution, and computer-aided protein design will further accelerate the speed of protein evolution and expand the scope for protein engineering. In this chapter we discuss general protein engineering strategies and advances in engineering proteins with desired functions, focusing on the "design" and "build" part of the design-build-test-learn cycle.

BIOMASS FUELS↗
DOE OSTI2023

Natural transformation as a tool in Acinetobacter baylyi : Evolution by amplification of gene copy number

For many years, the natural competency of Acinetobacter baylyi ADP1 facilitated studies of bacterial metabolism, biochemistry, and physiology. With the advent of synthetic biology, new opportunities arise to exploit the remarkable transformability and chromosomal plasticity of this model organism. In this chapter, we describe a recently developed method, “Evolution by Amplification and Synthetic Biology” (EASy). EASy allows the targeted amplification of chromosomal segments that give rise to new phenotypes. Increased gene dosage regulates protein expression in a rudimentary fashion by establishing a chromosomal array in which copy number adjusts via recombination between repeated DNA sequences. Selective conditions enrich for cells within the population that confer a growth advantage. Under continuous selective pressure, beneficial mutations may accumulate in any genomic region. Such mutations favor decreases in the average copy number of the target region. Thus, the genetic flexibility afforded by transient copy number variation helps accelerate the selection of engineered strains with desired traits during laboratory evolution. As a result, thanks to the extremely simple genetic manipulation of Acinetobacter baylyi ADP1, the EASy method can be readily implemented by researchers without the need for advanced instrumentation or complex cloning techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Chapter 20: Advances and Application of CRISPR-Cas Systems

A new gene-editing technique called clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins have revolutionized genome engineering because of its high efficiency, relatively low cost, and ease of use compared with other techniques such as zinc-finger nucleases and transcription activator-like effector nucleases. CRISPR-Cas systems have transformed biological research, quickly becoming the preferred method for engineering specific genome sequences in industrially relevant microbes, important food crops, and human cells. This powerful new tool has the potential for limitless applications ranging from the treatment of human diseases to improving food security to the generation of renewable and sustainable bioproducts and biofuels. In this chapter, we will discuss advances and applications for these CRISPR-Cas systems in biological engineering.

bacterial↗
DOE OSTI2024

Implementation of a realistic artificial data generator for crash data generation

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. In conclusion, the crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

42 ENGINEERING↗