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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Expansion of the tmRNA sequence database and new tools for search and visualization

Abstract Transfer–messenger RNA (tmRNA) contributes essential tRNA-like and mRNA-like functions during the process of trans-translation, a mechanism of quality control for the translating bacterial ribosome. Proper tmRNA identification benefits the study of trans-translation and also the study of genomic islands, which frequently use the tmRNA gene as an integration site. Automated tmRNA gene identification tools are available, but manual inspection is still important for eliminating false positives. We have increased our database of precisely mapped tmRNA sequences over 50-fold to 97 179 unique sequences. Group I introns had previously been found integrated within a single subsite within the TψC-loop; they have now been identified at four distinct subsites, suggesting multiple founding events of invasion of tmRNA genes by group I introns, all in the same vicinity. tmRNA genes were found in metagenomic archaeal genomes, perhaps a result of misbinning of bacterial sequences during genome assembly. With the expanded database, we have produced new covariance models for improved tmRNA sequence search and new secondary structure visualization tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Comparative Study on Deep Learning Methods for Defect Identification and Classification in Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of composite aerostructure material. Furthermore, the methods developed here are both highly reliable with a top recall value of 98.63% as well as extremely efficient requiring an average of 4 seconds during the inferencing stage to evaluate new composites.

composites↗
DOE OSTI2025

Power Quality and Load Capacity Evaluations of an Electric Vehicle for Multi-Robot System Applications

This paper evaluates the capability of a fully electric pickup truck, using the Ford F-150 Lightning as an example, to provide power to the circuit of a multi-robot system. The case study was conducted on a simulated INL Autonomous Pit Exploration System (APES) designed for the inspection of nuclear waste tank pits. Through a series of controlled tests, the vehicle’s power delivery consistency, load-handling capability, and battery performance were assessed under various conditions. First of all, the load test demonstrated that the vehicle provided stable power with low distortion and no unexpected interruptions. Second, during the operational limit test, the 240V system sustained loads up to 7.4 kW before tripping, providing insights into its operational limits. Last but not least, during a simulated full-scale APES operation, the vehicle’s battery depleted by only 6% over an hour, indicating sufficient capacity for extended use while retaining reserve power for transportation needs. This study highlights the potential of electric vehicles as reliable power sources for field operations, contributing to the advancement of sustainable technologies by reducing reliance on traditional fossil fuel generators and promoting the integration of clean energy solutions in remote and challenging environments.

Electric vehicle↗
DOE OSTI2024

Evaluating Model Robustness for Defect Identification and Classification in a Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from a composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating the composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of the composite aerostructure material. The methods developed here are both highly reliable with a top recall value of 98.64% as well as extremely efficient requiring an average of 4 s during the inferencing stage to evaluate new composites. Lastly, we investigate model robustness to concept drift by measuring its performance over time.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗
DOE OSTI2024

Optimization of a Welding Procedure for Making Critical Aluminum Welds on the LBNF Absorber Core Block

The LBNF Absorber consists of thirteen 6061-T6 aluminum core blocks. The core blocks are water cooled with de-ionized (DI) water which becomes radioactive during beam operations. The cooling water flows through gun-drilled channels in the core blocks. A weld quality optimization was performed to produce National Aeronautical Standard 1514 Class I quality welds on the aluminum core blocks. This was not successful in all cases. An existing Gas Tungsten Arc Welding Procedure Specification was fine tuned to minimize, in most cases, and eliminate detect-able tungsten inclusions in the welds. All the weld coupons, however passed welding inspection as per the piping code: ASME B31.3 Normal Fluid Service. Tungsten electrode diameter, type, and manufacturer were varied. Some of the samples were pre-heated and others were not. It was observed that larger diameter electrodes, 5/32 in., with pre-heated joints resulted in welds with the least number of tungsten inclusions. It is hypothesized that thinner electrodes breakdown easily and get lodged into the weld pool during the welding process. This breakdown is further enhanced by the large temperature differential between the un-preheated sample and the hot electrode.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Optimization of a Welding Procedure for Making Critical Aluminum Welds on the LBNF Absorber Core Block

he LBNF Absorber consists of thirteen 6061-T6 aluminum core blocks. The core blocks are water cooled with de-ionized (DI) water which becomes radioactive during beam operations. The cooling water flows through gun-drilled channels in the core blocks. A weld quality optimization was performed to produce National Aeronautical Standard (NAS) 1514 Class I quality welds on the aluminum core blocks. This was not successful in all cases. An existing Gas Tungsten Arc Welding (GTAW) Welding Procedure Specification (WPS) was fine tuned to minimize, in most cases, and eliminate detectable tungsten inclusions in the welds. All the weld coupons however, passed welding inspection as per the piping code: ASME B31.3 Normal Fluid Service. Tungsten electrode diameter, type, and manufacturer were varied. Some of the samples were pre-heated and others were not. It was observed that larger diameter electrodes, 5/32 in., with pre-heated joints resulted in welds with the least number of tungsten inclusions. It is hypothesized that thinner electrodes breakdown easily and get lodged into the weld pool during the welding process. This breakdown is further enhanced by the large temperature differential between the un-preheated sample and the hot electrode.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Data processing methods and data acquisition for samples larger than the field of view in parallel-beam tomography

Parallel-beam tomography systems at synchrotron facilities have limited field of view (FOV) determined by the available beam size and detector system coverage. Scanning the full size of samples bigger than the FOV requires various data acquisition schemes such as grid scan, 360-degree scan with offset center-of-rotation (COR), helical scan, or combinations of these schemes. Though straightforward to implement, these scanning techniques have not often been used due to the lack of software and methods to process such types of data in an easy and automated fashion. The ease of use and automation is critical at synchrotron facilities where using visual inspection in data processing steps such as image stitching, COR determination, or helical data conversion is impractical due to the large size of datasets. Here, we provide methods and their implementations in a Python package, named Algotom, for not only processing such data types but also with the highest quality possible. The efficiency and ease of use of these tools can help to extend applications of parallel-beam tomography systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Conceptual Design and Economic Assessment of a Chitin Biorefinery Based on Shrimp Processing Wastes

Due to the extensive production of shrimp in captivity, waste generation has increased significantly and has become an environmental problem. The recovery of biomolecules can be an important way to mitigate the environmental problems associated with processing in this sector. In this sense, the present work aimed to evaluate a biorefinery approach for valuing shrimp farming waste to obtain astaxanthin, chitin and chitosan. Stoichiometric segmentation was used as a tool to identify the process steps, whose information on process variables (fresh water consumption, flow rate and reaction conditions) was adapted from the literature. A biorefinery coupled to a shrimp processing plant was proposed for the immediate use of highly perishable biomass, to guarantee the quality of the extracted products and reduce storage and transportation costs. In practice, the biomass treatment sequence adopted (demineralization followed by deproteinization) eliminates the depigmentation step, as the chitin obtained has a lighter tone. The proposed route was evaluated for four scenarios based on two indicators: gross economic potential (EGP) and metrics for inspection of sales and reagents (MISR). The results indicate that economic viability is achieved only for the production of chitosan, resulting in a gross revenue of US$832.50/cycle and a MISR value > 1. The sale of astaxanthin promotes an increase of US$3.73/cycle in the EGP, considered too low for the inclusion of another stage in the process.

astaxanthin↗
DOE OSTI2020

Double-Shell Tank Primary Bottom Visual Inspection Results - 20025

A pressing need for the Double-Shell Tank Integrity Program at Hanford is of the ability to inspect the bottom of the tanks. Though the DSTs' annulus spaces (the space between the internal and external tank walls) have been inspected visually since 1992 and with Ultrasonic Testing (UT) since 1996, inspections of the tank bottoms have been able to be conducted due to limitations of available technology, omitting about 40 percent of the tank surface below the maximum fill level from routine inspection. Visual inspections of the tank annulus have been conducted up to five times in some DSTs and portions of the annulus space for all of the DSTs has been inspected twice with UT. This region includes the walls of the primary tank and secondary liner along with accessible portions of the secondary liner bottom. Due to this lack of technology, the degradation of the primary tank bottom in Tank AY-102 was undetected until the tank leaked into its annulus space, confirmed in 2012. Since that time, WRPS has been working with the nondestructive examination community and the Pacific Northwest National Laboratory, to evaluate potential technologies to conduct these challenging remote inspections. Recent work has included the development, testing, and deployment of several remote visual inspection technologies to observe the condition of the primary tank bottom of the DSTs by leveraging air distribution slots in the refractory pad on which it rests. Robotic solutions to conduct this inspection were developed with a detailed understanding of the physical configuration and operational logistics. Understanding and subsequent communication of these details to vendors within the robotics and nondestructive examination community was a critical component to the successful production of these new tools. Throughout the FY16-FY18 years, vendors from nondestructive examination community were solicited for ideas to meet the tank bottom inspection challenge. Two tank bottom visual inspection solutions were then pursued to meet that challenge. Both tools were successfully deployed at Tank AP-107, and provided valuable visuals, never before obtained from the under tank environment of a double-shell tank. While there are minor opportunities for improvement identified with each system, general outcomes were overwhelmingly positive. Both systems were successfully able to navigate the refractory air slot pattern from the outer edge to the tank center and record video footage. The micro-crawler provided high quality and very stable footage through the air slot pattern, but took longer to deploy into the slots and traverse through them than the alternative system. The push-pull tethered camera was able to navigate all seven of its target air slots in a matter of a few hours, which included deployment, movement between slot entrances, and complete removal of the system from the annulus environment. Through these air slots, new information was gained about the tank bottom and refractory pad condition of tank AP-107, AP-106, AP-108, and AN-102. While some debris was noted in the air slots, including sand, chipped refractory, and construction materials, the refractory was found to be structurally stable and adequately supporting the primary tank bottom through the full diameter of the tank. Primary tank bottom steel exterior was found to be in good condition, free of ongoing or aggressive corrosion conditions. Looking toward the future, robotic access to and visual inspection of refractory air slots and the primary tank bottom steel has now proven viable. Incorporating periodic air slot inspections as a regular practice within the Double-Shell Tank Integrity Program is the next step, allowing trending of any changes in condition. As ultrasonic testing infrastructure was leveraged to complete the initial system deployments described in this report, it makes sense to adopt that same strategy for ongoing periodic examinations and deploy these primary tank bottom inspection tools alongside ultrasonic testing operations. Development of visual inspection tools to evaluate the primary tank bottom region of the double-shell tanks was planned as the first stage of inspection. Continued development of volumetric sensors and incorporation of these inspection tools into Hanford's ongoing Double-Shell Tank Integrity Program are the next steps, seeking to continuously expand understanding of asset integrity and remaining useful life. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Laser Welded Burst Disk Weld Tooling

A production run of 5550 hermetically sealed cylinder assemblies with precision pressure relief burst discs will be assembled and laser welded at a manufacturing lab at Sandia National Labs. Production of these cylinder assemblies requires many steps, including piece part machining, geometric inspection, cleaning, subassembly, complete assembly via laser welding, and finally leak checking. While this production run is large enough to invest in process optimization and specialized tooling, it is not quite large enough to dedicate new lab space and specify equipment specifically for this job. This study will investigate process parameters and their effects on quality and process flow time, as well as a fixturing design study with the goal of reducing process time while maintaining quality requirements.

42 ENGINEERING↗
DOE OSTI2023

Status of the MQXFB Nb 3 Sn Quadrupoles for the HL-LHC

Here, the cold powering test of the first two prototypes of the MQXFB quadrupoles (MQXFBP1, now disassembled, and MQXFBP2), the Nb 3 Sn inner triplet magnets to be installed in the HL-LHC, has validated many features of the design, such as field quality and quench protection, but has found performance limitations. In fact, both magnets showed a similar phenomenology, characterized by reproducible quenches in the straight part inner layer pole turn, with absence of training and limiting the performance at 93% (MQXFBP1) and 98% (MQXFBP2) of the nominal current at 1.9 K, required for HL-LHC operation at 7 TeV. Microstructural inspections of the quenching section of the limiting coil in MQXFBP1 have identified fractured Nb 3 Sn sub-elements in strands located at one specific position of the inner layer pole turn, allowing to determine the precise origin of the performance limitation. In this paper we outline the strategy that has been defined to address the possible sources of performance limitation, namely coil manufacturing, magnet assembly and integration in the cold mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Plant Disease Detection Technology Assessment

Visual inspections by US Customs and Border Protection agriculture specialists have identified approximately 20,000 regulated, quarantined pests each year in agricultural products entering the United States. Most of these pests identified in the Agriculture Quarantine and Inspection (AQI) program are insects. Many pathogens are difficult to detect in agricultural products, particularly in early stages of infection. New technologies can help to detect plant pathogens and the diseases that they cause. This technology assessment was performed for the US Department of Homeland Security Science and Technology Directorate (DHS S&T) through the Food, Agriculture, and Veterinary Defense (FAV-D) program to identify emerging technologies that could address this hard problem. These emerging technologies differ in their diagnostic sensitivities and specificities, as well as in their measurement time and training requirements. New instruments that detect volatile organic compounds characteristic of plant disease or pathogens could provide a less invasive inspection method. Dogs, which can successfully detect many concealed agricultural products, have also been trained to detect some plant pests and pathogens. Simple immunological tests offer sensitive and specific detection of many pathogens at the point of use. Advanced imaging methods that use AI to sort fruits and vegetables and recognize anomalies at high speeds could be used in cooperation with exporters to improve food quality and reduce pests. Advances in nucleic acid–based detection methods that have become gold standards for confirmatory diagnostics are now making those methods available for faster, point-of-use detection. These new methods should be developed in the context of AQI operational requirements, which apply risk-based sampling protocols to protect agriculture and facilitate commerce and passenger transit.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ion Beam Figuring System for Synchrotron X-Ray Mirrors Achieving Sub-0.2-µrad and Sub-0.5-nm Root Mean Square

Abstract Optics with high-precision height and slope are increasingly desired in numerous industrial fields. For instance, Kirkpatrick–Baez (KB) mirrors play an important role in synchrotron X-ray applications. A KB system is composed of two aspherical, grazing-incidence mirrors used to focus an X-ray beam. The fabrication of KB mirrors is challenging due to the aspherical departure of the mirror surfaces from base geometries and the high-quality requirements for slope and height residuals. In this paper, we present the process of manufacturing an elliptical cylinder KB mirror using our in-house-developed ion beam figuring (IBF) and metrology technologies. First, the key aspects of figuring and finishing processes with IBF are illustrated in detail. The effect of positioning error on the convergence of the residual slope error is highlighted and compensated. Finally, inspection and cross-validation using different metrology instruments are performed and used as the final validation of the mirror. Results confirm that relative to the requested off-axis ellipse, the mirror has achieved 0.15-µrad root mean square (RMS) and 0.36-nm RMS residual slope and height errors, respectively, while maintaining the initial 0.3-nm RMS microroughness.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Novel Quantum Dot Technology Shows Promise in Simplifying Vehicle and Structural Surface Inspections

A team of researchers from both the Air Force Institute and Technology and Los Alamos National Laboratory are developing a paint that contains a material called quantum dots which can optically measure deformation of a surface. Quantum dots are the same materials used in new QLED television displays; however, they can also be used for a multitude of sensing applications such as deformation. The researchers used a new method of applying an interfacial layer between the quantum dot paint and the surface under investigation to help adhesion in harsh environments. The primary motivation behind this research is to make both quality assurance and maintenance of aircraft easier for the warfighter. The researchers’ efforts started in 2019 and are continuing. The technology works by shining a light onto the surface of the paint and the dots will emit back a wavelength of light that relates to the amount of deformation the surface is going through. This has the promise to allow for real-time 2D surface measurements that is more affordable than other 2D surface measurement alternatives.

42 ENGINEERING↗
DOE OSTI2025

Deep Learning Super-Resolution X-Ray Computed Tomography Algorithms for Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a nondestructive method for inspection and characterization of additively manufactured (AM) materials and parts. In practice, the resolution of XCT can be limited by factors such as detector binning, restricted field of view for large-scale objects, system blur, motion during scanning, and acquisition settings. These limitations can reduce the detectability of critical flaws such as pores, cracks, and lack of fusion. Super-resolution (SR) techniques offer a promising solution for improving the effective resolution and image quality of XCT reconstructions without the need for expensive hardware upgrades or laborious, time-consuming scans. In particular, deep learning-based SR methods have garnered attention in recent years as powerful tools for reconstructing high-resolution volumes from low-resolution inputs. In this work, a novel deep learning-based SR method is proposed for XCT scans of AM parts, and compared against several existing state-of-the-art (SOTA) methods. The proposed method, Simurgh-SR, is built on the pre-existing Simurgh framework and consists of a 2.5D U-Net trained to map low-quality inputs containing noise and artifacts to high-quality reconstructions characterized by higher flaw contrast, better noise texture, and reduced artifacts. The experimental results demonstrate superior performance of Simurgh-SR in performing 4× SR on real industrial XCT scans of thick 316L components, enhancing the structural similarity score and peak signal-to-noise ratio (>7dB) compared to the LR counterpart while improving the F1-score for flaw detection by more than 2.3× when compared to alternative SOTA SR methods. This improvement enables more accurate and significantly faster characterization of metal AM components. Additionally, Simurgh-SR was trained for both 2X and 4X SR and performs effectively at both levels, enabling the use of a single model for various SR factors.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗
DOE OSTI2023

Detecting and Characterizing Mg ii Absorption in DESI Survey Validation Quasar Spectra

Abstract We present findings of the detection of Magnesium II (Mg ii , λ = 2796, 2803 Å) absorbers from the early data release of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be at redshifts greater than z > 0.3, such that DESI would be able to observe an associated or intervening Mg ii absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects these systems through an initial line-fitting process and then confirms the line properties using a Markov Chain Monte Carlo sampler. Based upon a visual inspection of the resulting systems, we estimate that this sample has a purity greater than 99%. We have also investigated the completeness of our sample in regard to both the signal-to-noise properties of the input spectra and the rest-frame equivalent width ( W 0 ) of the absorber systems. From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg ii absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.8% implies a catalog at the completion of the five-year DESI survey that will contain over eight hundred thousand Mg ii absorbers. The cataloging of these systems will enable significant further research because they carry information regarding circumgalactic medium environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 ≤ z < 2.5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

Background: Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure. Results: We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena’s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset. Conclusions: BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena, together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data.

59 BASIC BIOLOGICAL SCIENCES↗