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All sources NASA NTRS DOE OSTI

NASA NTRS2007

Simulation of Unique Pressure Changing Steps and Situations in Psa Processes

A more rigorous cyclic adsorption process simulator is being developed for use in the development and understanding of new and existing PSA processes. Unique features of this new version of the simulator that Ritter and co-workers have been developing for the past decade or so include: multiple absorbent layers in each bed, pressure drop in the column, valves for entering and exiting flows and predicting real-time pressurization and depressurization rates, ability to account for choked flow conditions, ability to pressurize and depressurize simultaneously from both ends of the columns, ability to equalize between multiple pairs of columns, ability to equalize simultaneously from both ends of pairs of columns, and ability to handle very large pressure ratios and hence velocities associated with deep vacuum systems. These changes to the simulator now provide for unique opportunities to study the effects of novel pressure changing steps and extreme process conditions on the performance of virtually any commercial or developmental PSA process. This presentation will provide an overview of the cyclic adsorption process simulator equations and algorithms used in the new adaptation. It will focus primarily on the novel pressure changing steps and their effects on the performance of a PSA system that epitomizes the extremes of PSA process design and operation. This PSA process is a sorbent-based atmosphere revitalization (SBAR) system that NASA is developing for new manned exploration vehicles. This SBAR system consists of a 2-bed 3-step 3-layer system that operates between atmospheric pressure and the vacuum of space, evacuates from both ends of the column simultaneously, experiences choked flow conditions during pressure changing steps, and experiences a continuously changing feed composition, as it removes metabolic CO2 and H20 from a closed and fixed volume, i.e., the spacecraft cabin. Important process performance indicators of this SBAR system are size, and the corresponding CO2 and H20 removal efficiencies, and N2 and O2 loss rates. Results of the fundamental behavior of this PSA process during extreme operating conditions will be presented and discussed.

Ebner, Armin D.↗

NASA NTRS2010

Optimizing a Laser Process for Making Carbon Nanotubes

A systematic experimental study has been performed to determine the effects of each of the operating conditions in a double-pulse laser ablation process that is used to produce single-wall carbon nanotubes (SWCNTs). The comprehensive data compiled in this study have been analyzed to recommend conditions for optimizing the process and scaling up the process for mass production. The double-pulse laser ablation process for making SWCNTs was developed by Rice University researchers. Of all currently known nanotube-synthesizing processes (arc and chemical vapor deposition), this process yields the greatest proportion of SWCNTs in the product material. The aforementioned process conditions are important for optimizing the production of SWCNTs and scaling up production. Reports of previous research (mostly at Rice University) toward optimization of process conditions mention effects of oven temperature and briefly mention effects of flow conditions, but no systematic, comprehensive study of the effects of process conditions was done prior to the study described here. This was a parametric study, in which several production runs were carried out, changing one operating condition for each run. The study involved variation of a total of nine parameters: the sequence of the laser pulses, pulse-separation time, laser pulse energy density, buffer gas (helium or nitrogen instead of argon), oven temperature, pressure, flow speed, inner diameter of the flow tube, and flow-tube material.

Arepalli, Sivaram↗

NASA NTRS2010

Platform for Post-Processing Waveform-Based NDE

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

Roth, Don J.↗

NASA NTRS2006

Symmetric Phase Only Filtering for Improved DPIV Data Processing

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

Wernet, Mark P.↗

NASA NTRS2004

Chemical Thinning Process for Fabricating UV-Imaging CCDs

The thinning stage of the postfabrication process reported in the immediately preceding article is notable in its own right. Although the thinning process was described in the preceding article as part of an overall process of fabrication of a supported charge-coupled device (CCD), it is more generally applicable to both free-standing and supported devices that have been fabricated in die and wafer formats. Like the thermocompression bonding process described in the preceding article, the thinning process is compatible with CCD-fabrication processes, as well as postfabrication processes that enhance the response of CCDs to ultraviolet (UV) light, including the delta-doping process. CCDs that are thinned by this process and then delta-doped exhibit high quantum efficiencies that are stable with time and with exposure to the environment.

Jones, TOdd↗

NASA NTRS2011

Graphical Language for Data Processing

A graphical language for processing data allows processing elements to be connected with virtual wires that represent data flows between processing modules. The processing of complex data, such as lidar data, requires many different algorithms to be applied. The purpose of this innovation is to automate the processing of complex data, such as LIDAR, without the need for complex scripting and programming languages. The system consists of a set of user-interface components that allow the user to drag and drop various algorithmic and processing components onto a process graph. By working graphically, the user can completely visualize the process flow and create complex diagrams. This innovation supports the nesting of graphs, such that a graph can be included in another graph as a single step for processing. In addition to the user interface components, the system includes a set of .NET classes that represent the graph internally. These classes provide the internal system representation of the graphical user interface. The system includes a graph execution component that reads the internal representation of the graph (as described above) and executes that graph. The execution of the graph follows the interpreted model of execution in that each node is traversed and executed from the original internal representation. In addition, there are components that allow external code elements, such as algorithms, to be easily integrated into the system, thus making the system infinitely expandable.

Alphonso, Keith↗

NASA NTRS2014

High-Speed On-Board Data Processing for Science Instruments

A new development of on-board data processing platform has been in progress at NASA Langley Research Center since April, 2012, and the overall review of such work is presented in this paper. The project is called High-Speed On-Board Data Processing for Science Instruments (HOPS) and focuses on a high-speed scalable data processing platform for three particular National Research Council's Decadal Survey missions such as Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), Aerosol-Cloud-Ecosystems (ACE), and Doppler Aerosol Wind Lidar (DAWN) 3-D Winds. HOPS utilizes advanced general purpose computing with Field Programmable Gate Array (FPGA) based algorithm implementation techniques. The significance of HOPS is to enable high speed on-board data processing for current and future science missions with its reconfigurable and scalable data processing platform. A single HOPS processing board is expected to provide approximately 66 times faster data processing speed for ASCENDS, more than 70% reduction in both power and weight, and about two orders of cost reduction compared to the state-of-the-art (SOA) on-board data processing system. Such benchmark predictions are based on the data when HOPS was originally proposed in August, 2011. The details of these improvement measures are also presented. The two facets of HOPS development are identifying the most computationally intensive algorithm segments of each mission and implementing them in a FPGA-based data processing board. A general introduction of such facets is also the purpose of this paper.

Beyon, Jeffrey Y.↗

NASA NTRS2014

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.

Xilinx FPGA↗

NASA NTRS2015

Implementing NASA's Capability-Driven Approach: Insight into NASA's Processes for Maturing Exploration Systems

NASA is engaged in transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities focused on low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. Through pioneering, NASA seeks to address national goals to develop the capacity for people to work, learn, operate, live, and thrive safely beyond the Earth for extended periods of time. However, pioneering space involves more than the daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. This shift also requires a change in operating processes for NASA. The Agency can no longer afford to engineer systems for specific missions and destinations and instead must focus on common capabilities that enable a range of destinations and missions. NASA has codified a capability driven approach, which provides flexible guidance for the development and maturation of common capabilities necessary for human pioneers beyond LEO. This approach has been included in NASA policy and is captured in the Agency's strategic goals. It is currently being implemented across NASA's centers and programs. Throughout 2014, NASA engaged in an Agency-wide process to define and refine exploration-related capabilities and associated gaps, focusing only on those that are critical for human exploration beyond LEO. NASA identified 12 common capabilities ranging from Environmental Control and Life Support Systems to Robotics, and established Agency-wide teams or working groups comprised of subject matter experts that are responsible for the maturation of these exploration capabilities. These teams, called the System Maturation Teams (SMTs) help formulate, guide and resolve performance gaps associated with the identified exploration capabilities. The SMTs are defining performance parameters and goals for each of the 12 capabilities, developing maturation plans and roadmaps for the identified performance gaps, specifying the interfaces between the various capabilities, and ensuring that the capabilities mature and integrate to enable future pioneering missions. By managing system development through the SMTs instead of traditional NASA programs and projects, the Agency is shifting from mission-driven development to a more flexible, capability-driven development. The process NASA uses to establish, integrate, prioritize, and manage the SMTs and associated capabilities is iterative. NASA relies on the Human Exploration and Operation Mission Directorate's SMT Integration Team within Advanced Exploration Systems to coordinate and facilitate the SMT process. The SMT Integration team conducts regular reviews and coordination meetings among the SMTs and has developed a number of tools to help the Agency implement capability driven processes. The SMT Integration team is uniquely positioned to help the Agency coordinate the SMTs and other processes that are making the capability-driven approach a reality. This paper will introduce the SMTs and the 12 key capabilities they represent. The role of the SMTs will be discussed with respect to Agency-wide processes to shift from mission-focused exploration to a capability-driven pioneering approach. Specific examples will be given to highlight systems development and testing within the SMTs. These examples will also show how NASA is using current investments in the International Space Station and future investments to develop and demonstrate capabilities. The paper will conclude by describing next steps and a process for soliciting feedback from the space exploration community to refine NASA's process for developing common exploration capabilities.

Williams-Byrd, Julie↗

NASA NTRS2019

Potential Improvements to the Nuclear Safety and Launch Approval Process for Nuclear Reactors Utilized for Space Power and Propulsion Applications

This study examines potential improvements that could be made to the nuclear safety and launch approval process for fission reactors to reduce the associated uncertainties in cost and schedule while continuing to ensure public safety and environmental protection. It concentrates on the launch approval and mission safety of fission power and propulsion applications of nuclear energy. Improvements to the launch approval process for radioisotope power systems (RPSs) are being considered elsewhere but are acknowledged throughout the report. The study considered technical, process, and organizational improvements to the launch approval processes. The study exclusively evaluated reactors that would not be started up prior to achieving a “sufficiently high orbit,” per United Nations (UN) Resolution 47/68.Potential criticality accidents were considered that could occur during a launch failure or abort or during reentry. Numerous scenarios were examined that might involve one or more Earth flybys as well as potential transportation missions that could intentionally return an active, or previously active fission reactor to Earth orbit. The Study Group was guided in its deliberations according to a number of fundamental principles. These included the paramount importance of adequate and appropriate levels of public safety and environmental protection as well as the importance of the inclusion of independent scientific, engineering, and safety reviews of the applications and proposals as a critical part of the process. Also considered was the need for the development of launch approval processes that might be different, depending upon the source of the application for launch approval, whether it be derived as a governmental launch, a commercial launch, or a hybrid/combination of the two. It is clear that all launches of nuclear reactors into space should have similar safety requirements; however, the safety review effort and the details of the analysis that are required should be commensurate with the potential hazards and the actual risk, which may differ based on the reactor design and its intended purpose. Finally, the study aimed at ensuring that whatever processes and procedures are developed should maximize the sufficiency, simplicity, and transparency of the processes. The Study Group reached five Conclusions and makes thirteen Recommendations. The Conclusions and Recommendations presented here are extensions of those presented previously in other studies. This report attempts to add specificity to the actions that need to be taken in order to move forward with successful space fission reactor programs. Without action to address the perceived and real problems in the launch approval process, designers and mission managers will be reluctant to commit the resources necessary to make space fission reactors a reality.

Camp, Allen↗

NASA NTRSDate not supplied

Transcriptomics Processing Pipelines for Space Biology: An Open Source and Consensus-Driven Approach

Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.

Jonathan Oribello↗

NASA NTRSDate not supplied

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗

DOE OSTI2024

Comparison of Silicon Decarbonization Methods to Reduce Process Emissions and Energy Consumption

The demand for silicon is rising due to its use in solar cells, electronics, and alloying as part of the green transition. However, these products require silicon metal (metallurgical grade silicon, >98% Si) as their main raw material before undergoing further chemical refining, usually via gas phase in methods such as the Siemens process. Silicon metal is currently produced in a submerged arc furnace via carbothermic reduction of quartz, which results in 10-12 tCO2/tSi. More than 40% of these emissions are process emissions, meaning they do not include contributions from electricity generation or transport. This talk will discuss promising methods to reduce or eliminate these process emissions. These include the use of biocarbon and carbon capture, aluminothermic reduction, electrochemical reduction with molten salts, and use of hydrogen in a modified Siemens process. Biocarbon and carbon capture is a straightforward method to reduce the net carbon emissions of the process, but long-term sustainable production of high-quality charcoal is a challenge. Aluminothermic reduction makes good use of aluminum byproducts such as dross but is perhaps limited in its applications to aluminum-silicon alloy products. Electrochemical reduction is promising as a method of producing high purity Si from quartz, without further need for the Siemens process, but is still in early stages of research and slow processing times are a concern. Finally, the use of hydrogen in a modified Siemens process would also result in a high purity Si product from quartz, however the process has considerable logistical challenges with corrosive and unstable gases at high temperatures. This talk will further expand on the potential merits and challenges of each method, while comparing their potential to reduce emissions and/or energy consumption while meeting global demand.

decarbonization↗

DOE OSTI2025

A fast computational framework for the design of solvent-based plastic recycling processes

Multicomponent plastics cannot be processed using mechanical recycling technologies, hindering efforts to deal with plastic waste. Multicomponent plastics include multilayer plastic films, which are widely used for food and healthcare packaging. Multilayer films combine several layers (potentially dozens) of different polymers to protect products from external factors (e.g., oxygen, water, temperature, shock, and light). Solvent-based separation processes have emerged as a promising alternative to recycle these complex materials. For instance, the Solvent-Targeted Recovery and Precipitation (STRAP TM ) process uses sequential solvent washes to selectively dissolve and separate constituent polymers from multicomponent plastic waste, including films. STRAP TM process design (separation sequence, type of solvents, and operating conditions) changes significantly depending on the design of the multilayer plastic film (e.g., number, types, and proportions of polymers). The ability to quickly quantify the economic and environmental benefits of diverse STRAP TM process designs is essential to accelerate the development of sustainable recycling processes and more recyclable multilayer film products. In this work, we present a fast computational framework that integrates molecular-scale models, process modeling, and techno-economic and life cycle analysis to quickly evaluate STRAP TM designs. The computational framework is general and can be used to study the processing of complex multilayer plastic waste streams that contain many layers. Furthermore, we highlight the different uses of the framework via targeted case studies.

Computational framework↗

DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗

DOE OSTI2025

Transformational Sorbent-Based Process for a Substantial Reduction in the Cost of CO2 Capture

Adsorption processes have the potential to significantly reduce the CO2 capture cost from power plants and industrial flue gases. InnoSepra has developed several sorbent-based technologies to obtain very high CO2 recovery and high purity CO2 while meeting the EOR/sequestration product specifications. A first-generation process was shown to achieve CO2 recoveries greater than 94% at CO2 purities in the range of 98.5-99.5%. The absolute heat energy required for the process was not only 40% lower than MEA but also was needed at a much lower temperature. This work will present the performance of the second-generation InnoSepra process which is based on a breakthrough sorbent regeneration method. This process has a projected 45% lower capital cost compared to MEA, less than 16% loss in plant output for CO2 capture and compression, and a CO2 capture cost at least 55% lower than MEA. Lab scale testing and the process simulations indicate a CO2 capture performance similar to or better than the first-generation process. Pilot scale drying and breakthrough tests were carried out at the Technology Centre Mongstad (TCM), Norway, and lab-scale cyclic tests were carried out at InnoSepra to confirm the process improvement. During these tests, InnoSepra’s flue gas purification technology was also tested at TCM. It can provide a low-cost option for the removal of NO2 and SOX to sub-ppm levels as well as a significant reduction in aerosol emissions.

08 HYDROGEN↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method

The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.

316 L Stainless Steel↗

NASA NTRSDate not supplied

The Additive Manufacturing Moment Measure - A Parallel Computation Technique for Determining Build Variance in the Laser Powder Bed Fusion Process

Additive manufacturing (AM) has unique process attributes that facilitate the creation of optimized, complex, and unique parts for aerospace applications. However, the multi-scale and complicated building process for AM parts can cause unexpected build conditions that result in microstructural variability within the deposited material. The need for richer datasets and computational modeling capabilities to improve AM process reliability is a consequence of this microstructural variability. A computational approach, referred to as the Additive Manufacturing Moment Measure (AM3), addresses this need by leveraging the way AM processes fuse material in precise, incremental steps. During the layering sequence, each previous step contributes to the condition of the current step at the center of the heat source. The precise steps can be selected to systematically create a time-space point field with co-located machine input and in-situ sensor data. The sequential nature of the AM process, coupled with nearest neighbor calculations, allows for a fully parallel computation for part-scale build profile analysis. The AM3 concept introduced here enables part-scale assessment directly from build files and in-situ process monitoring sensors alike. The AM moment measures were calculated for build point fields and compared with co-located in-situ and ex-situ nondestructive evaluation and optical microscopy observations. These comparisons permit a better understanding of how the sequential process actions can affect the quality of a laser powder bed fusion (LPBF) build. Details of the AM3technique will be discussed and compared to measured LPBF part characteristics. The AM3 results indicate a strong potential to advance the qualification process for aerospace applications.

Additive Manufacturing↗