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At least 595 records · Page 33

Climate, air quality, and equity benefits from hydrogen substitution for fossil fuels used in process heat

Fossil fuel combustion for process heat in heavy industry accounts for ~15% of all United States CO 2 emissions and emits PM 2.5 and its precursors, emissions that have a disproportionate impact on minority populations. Decarbonizing process heat in the U.S. via hydrogen substitution presents an opportunity to reduce emissions of CO 2 and PM 2.5 and mitigate resulting exposure disparity. Here, we show that hydrogen substitution in steelmaking provides a large reduction in CO 2 emissions and air quality-related premature mortality, while hydrogen substitution in petroleum refining substantially benefits disadvantaged communities. When reductions in CO 2 emissions and premature mortality are monetized using standard regulatory values, we find that the sum of air pollution and climate benefits outweighs the difference in private cost associated with hydrogen substitution in steelmaking, regardless of the method of hydrogen production. The approach developed here can support evaluations of equity-focused decarbonization strategies in other industries and for specific sites.

08 HYDROGEN↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

Incorporating Handling Qualities Analysis into Rotorcraft Conceptual Design

This paper describes the initial development of a framework to incorporate handling qualities analyses into a rotorcraft conceptual design process. In particular, the paper describes how rotorcraft conceptual design level data can be used to generate flight dynamics models for handling qualities analyses. Also, methods are described that couple a basic stability augmentation system to the rotorcraft flight dynamics model to extend analysis to beyond that of the bare airframe. A methodology for calculating the handling qualities characteristics of the flight dynamics models and for comparing the results to ADS-33E criteria is described. Preliminary results from the application of the handling qualities analysis for variations in key rotorcraft design parameters of main rotor radius, blade chord, hub stiffness and flap moment of inertia are shown. Varying relationships, with counteracting trends for different handling qualities criteria and different flight speeds are exhibited, with the action of the control system playing a complex part in the outcomes. Overall, the paper demonstrates how a broad array of technical issues across flight dynamics stability and control, simulation and modeling, control law design and handling qualities testing and evaluation had to be confronted to implement even a moderately comprehensive handling qualities analysis of relatively low fidelity models. A key outstanding issue is to how to 'close the loop' with an overall design process, and options for the exploration of how to feedback handling qualities results to a conceptual design process are proposed for future work.

Analysis into Rotorcraft↗

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms​ ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

A New Route Toward Atomically Flat and Defect-Free Ge/SiGe Planar Heterostructures

Germanium-based planar heterostructures are emerging as versatile platforms for realizing quantum devices. In particular, planar Ge/SiGe quantum wells (QWs) host hole states with exceptionally high mobility and strong, electrically tunable spin–orbit interactions, enabling full electrical control of quantum information. A key requirement for these systems is the growth of microscopic, defect-free, atomically flat Ge QW heterostructures on relaxed or reverse-graded SiGe buffer layers, as well as on commercial Ge substrates. While several physical deposition techniques have demonstrated high-quality planar Ge/SiGe QWs, a major challenge remains: minimizing defect density typically requires high growth temperatures, which are incompatible with standard CMOS process flows. Here, we present a convenient low-temperature process for realizing high-quality planar SiGe/Ge heterostructures using a combination of thermal and electron-beam evaporation. We systematically map the effects of ex-situ and in-situ substrate preparation protocols, growth temperature, and post-deposition annealing conditions, and correlate these parameters with surface roughness and defect density. We find that in-situ oxide desorption conditions and post-annealing parameters have the most pronounced impact on improving surface quality. Under optimized conditions, we achieve atomically smooth surfaces with root-mean-square roughness σrms​ ≤ 10 Å and negligible defect density. Interestingly, thermally evaporated Ge layers exhibit oriented triangular crystallites that elongate upon post-annealing in the presence of high Ge vapor pressure. These results demonstrate that this simple, low-temperature deposition approach is a viable and effective route for achieving high-quality Ge QW heterostructures, with strong potential for scalable quantum computing and sensing applications.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

Launch vehicle systems design analysis

Current launch vehicle design emphasis is on low life-cycle cost. This paper applies total quality management (TQM) principles to a conventional systems design analysis process to provide low-cost, high-reliability designs. Suggested TQM techniques include Steward's systems information flow matrix method, quality leverage principle, quality through robustness and function deployment, Pareto's principle, Pugh's selection and enhancement criteria, and other design process procedures. TQM quality performance at least-cost can be realized through competent concurrent engineering teams and brilliance of their technical leadership.

Ryan, Robert↗

Laboratory for Atmospheres 2002 Technical Highlights

How can we improve our ability to predict the weather-tomorrow, next week, and into the future? How is the Earth's climate changing? What causes such change? And what are its costs? What can the atmospheres of distant planets teach us about our own planet and its evolution? The Laboratory for Atmospheres is helping to answer these and other scientific questions about our planet and its neighbors. The Laboratory conducts a broad theoretical and experimental research program studying all aspects of the atmospheres of the Earth and other planets, including their structural, dynamical, radiative, and chemical properties, with the overarching goal to provide better understanding and to improve prediction of the Earth's climate. Vigorous research is central to NASA's exploration of the frontiers of knowledge. NASA scientists play a key role in conceiving new space missions, providing mission requirements, and carrying out research to explore the behavior of planetary systems, including, notably, the Earth's. Our Laboratory's scientists also supply outside scientists with technical assistance and scientific data to further investigations not immediately addressed by NASA itself. Laboratory scientists submit competitive research proposals with diverse scientific or technological approaches to NASA and other Federal agencies to acquire research support. The Laboratory management strives to provide a working environment that promotes creativity, competition, and openness. The Laboratory for Atmospheres is a vital participant in NASA's research program. Our Laboratory often has relatively large programs, sizable satellite missions, or observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists' responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. The Laboratory places high importance on promoting and measuring quality in its scientific research. We strive to assure high quality through peer-review funding processes that support approximately 90% of the work in the Laboratory. The overall quality of our scientific efforts is evaluated periodically by committees of advisors from the external scientific community, as detailed in Appendix 2 of this document. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public's awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. Section 6 presents details of the Laboratory's outreach activities during 2002. The Laboratory is also committed to addressing the demographic imbalances that exist today in the atmospheric and space sciences. We must address these imbalances for our field to enjoy the full benefit of all of the Nation's talent. The Laboratory makes substantial efforts to attract new scientists to the fields of atmospheric and space sciences. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of Earth sciences.

Steven E. Platnick↗

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗

The Marshall Automated Weld System (MAWS)

A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer-controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.

Russell, Carolyn K.↗

The Marshall Automated Weld System (MAWS)

A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.

Russell, Carolyn K.↗

CRN5EXP: Expert system for statistical quality control

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

Hentea, Mariana↗

Software Quality Assurance Plan: Cardinal

The Cardinal Software Quality Assurance (SQA) Program aims to provide the controls and processes necessary to enable continuous, high-quality software development while meeting user and program sponsor requirements. This SQA Plan (SQAP) delineates the SQA Program framework for Cardinal by describing the Program activities, organization, and documentation, and by clearly defining the interconnection of all Program items. It should be noted that this SQAP is aligned with the current version of the Argonne Quality Assurance Program Plan, which was designed to align with DOE O 414.1D. This SQAP is also aligned with the revision 10 of the SQAP for MOOSE and MOOSE-based applications.

97 MATHEMATICS AND COMPUTING↗

Furnace Tubes For Depositing Parylene-N(TM) On Hgl(2) Crystals

Shapes of quartz pyrolysis tubes used to deposit Parylene-N on Hgl(2) crystals modified to improve quality of coating. Use of zigzag tube, along with higher processing temperature, resulted in coating of better quality, including greater transparency and more uniformity of appearance. In addition, longer path taken by dimer in passing by baffles increases time spent in high-temperature region, increasing degree of cracking even more.

Iwanczyk, Jan S.↗

External Tank - The Structure Backbone

The External Tank forms the structural backbone of the Space Shuttle in the launch configuration. Because the tank flies to orbital velocity with the Space Shuttle Orbiter, minimization of weight is mandatory, to maximize payload performance. Choice of lightweight materials both for structure and thermal conditioning was necessary. The tank is large, and unique manufacturing facilities, tooling, handling, and transportation operations were required. Weld processes and tooling evolved with the design as it matured through several block changes, to reduce weight. Non Destructive Evaluation methods were used to assure integrity of welds and thermal protection system materials. The aluminum-lithium alloy was used near the end of the program and weld processes and weld repair techniques had to be refined. Development and implementation of friction stir welding was a substantial technology development incorporated during the Program. Automated thermal protection system application processes were developed for the majority of the tank surface. Material obsolescence was an issue throughout the 40 year program. The final configuration and tank weight enabled international space station assembly in a high inclination orbit allowing international cooperation with the Russian Federal Space Agency. Numerous process controls were implemented to assure product quality, and innovative proof testing was accomplished prior to delivery. Process controls were implemented to assure cleanliness in the production environment, to control contaminants, and to preclude corrosion. Each tank was accepted via rigorous inspections, including non-destructive evaluation techniques, proof testing, and all systems testing. In the post STS-107 era, the project focused on ascent debris risk reduction. This was accomplished via stringent process controls, post flight assessment using substantially improved imagery, and selective redesigns. These efforts were supported with a number of test programs to simulate combined environments. Processing improvements included development and use of low spray guns for foam application, additional human factors considerations for production, use of high fidelity mockups during hardware processing with video review, improved tank access, extensive use of non destructive evaluation, and producibility enhancements. Design improvements included redesigned bipod fittings, a bellows heater, a feedline camera active during ascent flight, removal of the protuberance airload ramps, redesigned ice frost ramps, and titanium brackets replaced aluminum brackets on the liquid oxygen feedline. Post flight assessment improved due to significant addition of imagery assets, greatly improving situational awareness. The debris risk was reduced by two orders of magnitude. During this time a major natural disaster was overcome when Katrina damaged the manufacturing facility. Numerous lessons from these efforts are documented within the paper.

Welzyn, Kenneth↗

Technology Infusion Challenges from a Decision Support Perspective

In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

Adumitroaie, V.↗

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗

Can Solution Supersaturation Affect Protein Crystal Quality?

The formation of large protein crystals of "high quality" is considered a characteristic manifestation of microgravity. The physical processes that predict the formation of large, high quality protein crystals in the microgravity environment of space are considered rooted in the existence of a "depletion zone" in the vicinity of crystal. Namely, it is considered reasonable that crystal quality suffers in earth-grown crystals as a result of the incorporation of large aggregates, micro-crystals and/or large molecular weight "impurities", processes which are aided by density driven convective flow or mixing at the crystal-liquid interface. Sedimentation and density driven convection produce unfavorable solution conditions in the vicinity of the crystal surface, which promotes rapid crystal growth to the detriment of crystal size and quality. In this effort, we shall further present the hypothesis that the solution supersaturatoin at the crystal surface determines the growth mechanism, or mode, by which protein crystals grow. It is further hypothesized that protein crystal quality is affected by the mechanism or mode of crystal growth. Hence the formation of a depletion zone in microgravity environment is beneficial due to inhibition of impurity incorporatoin as well as preventing a kinetic roughening transition. It should be noted that for many proteins the magnitude of neither protein crystal growth rates nor solution supersaturation are predictors of a kinetic roughening transition. That is, the kinetic roughening transition supersaturation must be dtermined for each individual protein.

Gorti, Sridhar↗

Practical procedures for sensor quality assessment

Sensors are increasingly deployed for process monitoring and control. These produce on-line measurements at a high frequency, in parallel with low-frequency laboratory measurements. Compared to laboratory practices, sensor data quality assessment and control practices are far less structured at most utilities. This leads to inaccurate sensor data with unknown uncertainty factors.This chapter shows how to establish standard operating procedures (SOPs) to support sensor data quality assessment and control and subsequent maintenance actions by producing relevant sensor metadata. Furthermore, SOPs are provided for the most commonly used wastewater quality sensors, inspired by utility and academic best practices. This chapter builds on definitions provided in Chapter 3 and provides additional definitions specifically related to sensors maintenance. Chapter 6 complements the methods in this chapter, which are based on reference measurements, with data-analytical techniques.

Alferes, Janelcy↗