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All sources NASA NTRS DOE OSTI

DOE OSTI2015

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, which were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗

DOE OSTI2021

Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Processed Data, Cook Inlet, AK, 2021

This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Energy Oceanographic Mooring (THEOM) bottom lander and two Mid-Water Mooring (MWM) Stablemoor buoys from 1 July 2021 to 31 August 2021 (60 days). The west-most mooring (MWM1) was deployed at 60.720225 N, 151.436196 W in ~50 m of water. The middle mooring (THEOM) was deployed at 60.720703 N, 151.429500 W in ~52 m of water. The east-most buoy (MWM2) was deployed at 60.720081 N, 151.420896 W in ~50 m of water. Each Stablemoor carried three instruments: 1. A Nortek Vector acoustic Doppler velocimeter (ADV) mounted at the Stablemoor's nose. Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was motion-corrected using the internal IMU and external ADCP bottom-track data and then bin-averaged into 4 minute bins and converted to the Principal (streamwise, cross-stream, vertical) coordinate system. (Note: 30 seconds were trimmed from the beginning and end of each 5 minute duty cycle to account for the filter end-effects from turning on and turning off the IMU.) 2. A down-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the first Stablemoor instrument well. Data were recorded in 2 Hz with 5-beam burst and bottom-track enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. 3. An up-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the second Stablemoor instrument well. Data were recorded at 4 Hz with 5 beam burst enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. Note: the down-facing ADCP on MWM1 failed on July 10th, 2021, only recording 9 days of data. Because ADV motion-correction required bottom track, the ADV from MWM1 also only has 9 days processed. Additionally, only 25 days of data were processed from the MWM2 ADV because it appeared to have been impacted by debris on 7/25. Two instruments were mounted on the THEOM (see MHKDR link further below for THEOM raw data): 4. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was bin-averaged into 5 minute bins, and converted to the Principal coordinate system. 5. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 10 minutes bins and converted to the Principal coordinate system.

16 TIDAL AND WAVE POWER↗

DOE OSTI2014

Data Preparation Process for the Buildings Performance Database

The Buildings Performance Database (BPD) includes empirically measured data from a variety of data sources with varying degrees of data quality and data availability. The purpose of the data preparation process is to maintain data quality within the database and to ensure that all database entries have sufficient data for meaningful analysis and for the database API. Data preparation is a systematic process of mapping data into the Building Energy Data Exchange Specification (BEDES), cleansing data using a set of criteria and rules of thumb, and deriving values such as energy totals and dominant asset types. The data preparation process takes the most amount of effort and time therefore most of the cleansing process has been automated. The process also needs to adapt as more data is contributed to the BPD and as building technologies over time. The data preparation process is an essential step between data contributed by providers and data published to the public in the BPD.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Progress on the evolution of the pilot scale manufacturing plant and initial results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Construction of the pilot scale manufacturing plant has been completed and results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Integrating Cyber-Informed Engineering into Process Automation

As organizations increasingly automate their core missions and essential functions to address business risks and enhance efficiency, process automation becomes pivotal. This shift, involving minimal or no manual intervention, significantly impacts an organization's cyber-risk landscape. While automation drives efficiencies, it also introduces new cyber risks if not properly managed. Cyber-Informed Engineering (CIE) provides a proactive framework for managing these digital risks, enhancing cyber-resilience in process automation. This document supports organizations in applying CIE principles to mitigate the cyber risks associated with automation. The outlined approach can be independently implemented to improve any organization’s cyber-resilience, ensuring that the advantages of automation do not result in unaddressed or unmanaged digital risks. It serves as a starting point, offering considerations for integrating CIE principles and practices into organizational processes. CIE is presented as an iterative process, fostering continuous improvement and reinforcing the engineering and operational cultures to manage digital risks effectively. The document is structured as follows: Section 1 provides background on CIE and process automation, and their integration. Section 2 explores the twelve CIE principles in the context of process automation, highlighting key questions, engineering considerations, and implications for digital risk management. Section 3 synthesizes the findings and offers recommendations to advance resilience by design.

42 - ENGINEERING↗

DOE OSTI2026

Solar Thermal Energy Planner (STEP 1): A New Decision Support Tool for Solar Industrial Process Heat Applications

Solar thermal technologies are a promising technology to supply low-cost thermal energy to industrial processes, but there are often significant barriers to entry to industrial owners considering these technologies for their energy demands. To overcome this barrier and convey economic value to customers, NREL and Sandia National Laboratories developed Solar Thermal Energy Planner (STEP 1), a new web-based decision support tool for solar industrial process heat systems. At SolarPACES 2024, the STEP 1 tool was still under development; progress, methodologies, and a preliminary case study was presented. With the STEP 1 tool launch in May 2025, in this work, the initial version of the full public tool will be presented with demonstrations of its capabilities using a few case studies. First, the user's process heat needs such as location, process media (e.g., steam, air), process temperature, land availability, electricity and fuel costs, among other parameters. STEP 1 features a mapping interface that allows users to draw land and roof boundaries. The process media and temperature inform technology selection criteria modules that determine the appropriate solar thermal collection technologies, as well as congruent heat transfer media (e.g., hot water, oil, salt). Once the solar thermal technology selected, its nominal thermal production for the given site is characterized using NREL's System Advisor Model (SAM). Then, a modified version of NREL's REopt optimal sizing and dispatch optimization tool determines cost-optimal sizing. Within minutes, the user receives the results of the technoeconomics analysis, including the size and performance of the cost-optimal solar-plus-storage system. The cost of the system is compared to business-as-usual (e.g., an existing, standalone natural gas boiler). Users can download key results to store for sensitivity analyses. Examples of flat plate collector, parabolic trough, and molten salt tower applications with and without PV hybridization for different industrial facility types are presented in this work. The STEP 1 tool aims to reduce barriers to the adoption of solar heating solutions stemming from a lack of familiarity and technical background with solar system design options and costs among industry stakeholders.

14 SOLAR ENERGY↗

DOE OSTI2016

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

respiration↗

DOE OSTI2024

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

ON THE r -PROCESS ENRICHMENT OF DWARF SPHEROIDAL GALAXIES

Recent observations of Reticulum II have uncovered an overabundance of r -process elements compared to similar ultra-faint dwarf spheroidal galaxies (UFDs). Because the metallicity and star formation history of Reticulum II appear consistent with all known UFDs, the high r -process abundance of Reticulum II suggests enrichment through a single, rare event, such as a double neutron star (NS) merger. However, we note that this scenario is extremely unlikely, as binary stellar evolution models require significant supernova natal kicks to produce NS–NS or NS–black hole (BH) mergers, and these kicks would efficiently remove compact binary systems from the weak gravitational potentials of UFDs. We examine alternative mechanisms for the production of r -process elements in UFDs, including a novel mechanism wherein NSs in regions of high dark matter (DM) density implode after accumulating a BH-forming mass of DM. We find that r -process proto-material ejection by tidal forces, when a single NS implodes into a BH, can occur at a rate matching the r -process abundance of both Reticulum II and the Milky Way. Remarkably, DM models which collapse a single NS in observed UFDs also solve the missing pulsar problem in the Milky Way Galactic Center. We propose tests specific to DM r -process production which may uncover or rule out this model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Contribution of neutron star mergers to the r-process chemical evolution in the hierarchical galaxy formation

The main astronomical source of r-process elements has not yet been identified. One plausible site is neutron star mergers (NSMs), but from the perspective of the Galactic chemical evolution, it has been pointed out that NSMs cannot reproduce the observed r-process abundance distribution of metal-poor stars at [Fe/H]<−3. Recently, Tsujimoto and Shigeyama pointed out that NSM ejecta can spread into a much larger volume than ejecta from a supernova. We re-examine the enrichment of r-process elements by NSMs considering this difference in propagation using the chemical evolution model under the hierarchical galaxy formation. The observed r-process enhanced stars around [Fe/H]∼−3 are reproduced if the star formation efficiency is lower for low-mass galaxies under a realistic delay-time distribution for NSMs. We show that a significant fraction of NSM ejecta escape from its host proto-galaxy to pollute intergalactic matter and other proto-galaxies. The propagation of r-process elements over proto-galaxies changes the abundance distribution at [Fe/H]<−3 and obtains distribution compatible with observations of the Milky Way halo stars. In particular, the pre-enrichment of intergalactic medium explains the observed scarcity of extremely metal-poor stars without Ba and abundance distribution of r-process elements at [Fe/H]≲−3.5.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Formation of Globular Clusters with Internal Abundance Spreads in r -Process Elements: Strong Evidence for Prolonged Star Formation

Several globular clusters (GCs) in the Galaxy are observed to show internal abundance spreads in r -process elements (e.g., Eu). We propose a new scenario that explains the origin of these GCs (e.g., M5 and M15). In this scenario, stars with no/little abundance variations first form from a massive molecular cloud (MC). After all of the remaining gas of the MC is expelled by numerous supernovae, gas ejected from asymptotic giant branch stars can be accumulated in the central region of the GC to form a high-density intracluster medium (ICM). Merging of neutron stars then occurs to eject r -process elements, which can be efficiently trapped in and subsequently mixed with the ICM. New stars formed from the ICM can have r -process abundances that are quite different from those of earlier generations of stars within the GC. This scenario can explain both (i) why r -process elements can be trapped within GCs and (ii) why GCs with internal abundance spreads in r -process elements do not show [Fe/H] spreads. Our model shows (i) that a large fraction of Eu-rich stars can be seen in Na-enhanced stellar populations of GCs, as observed in M15, and (ii) why most of the Galactic GCs do not exhibit such internal abundance spreads. Our model demonstrates that the observed internal spreads of r -process elements in GCs provide strong evidence for prolonged star formation (∼10{sup 8} yr).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

r-Process Radioisotopes from Near-Earth Supernovae and Kilonovae

The astrophysical sites where r-process elements are synthesized remain mysterious: it is clear that neutron star mergers (kilonovae (KNe)) contribute, and some classes of core-collapse supernovae (SNe) are also possible sources of at least the lighter r-process species. The discovery of 60Fe on the Earth and Moon implies that one or more astrophysical explosions have occurred near the Earth within the last few million years, probably SNe. Intriguingly, 244 Pu has now been detected, mostly overlapping with 60 Fe pulses. However, the 244 Pu flux may extend to before 12 Myr ago, pointing to a different origin. Here, motivated by these observations and difficulties for r-process nucleosynthesis in SN models, we propose that ejecta from a KN enriched the giant molecular cloud that gave rise to the Local Bubble, where the Sun resides. Accelerator mass spectrometry (AMS) measurements of 244 Pu and searches for other live isotopes could probe the origins of the r-process and the history of the solar neighborhood, including triggers for mass extinctions, e.g., that at the end of the Devonian epoch, motivating the calculations of the abundances of live r-process radioisotopes produced in SNe and KNe that we present here. Given the presence of 244 Pu, other r-process species such as 93 Zr, 107 Pd, 129 I, 135 Cs, 182 Hf, 236 U, 237 Np, and 247 Cm should be present. Their abundances and well-resolved time histories could distinguish between the SN and KN scenarios, and we discuss prospects for their detection in deep-ocean deposits and the lunar regolith. We show that AMS 129 I measurements in Fe–Mn crusts already constrain a possible nearby KN scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Possibility to Identify the Contributions from Collapsars, Supernovae, and Neutron Star Mergers from the Evolution of the r-process Mass Abundance Distribution

We study the evolution of rapid neutron-capture process (r-process) isotopes in the galaxy. We analyze relative contributions from core-collapse supernovae (CCSNe), neutron star mergers, and collapsars under a range of astrophysical conditions and nuclear input data. Here we show that, although the r-process in each of these sites can lead to a similar (universal) elemental distribution, the detailed isotopic abundances can differ from one site to another. These differences may allow for the identification of which sources contributed to the early evolution of r-process material in the galaxy. Our simulations suggest that the early evolution was dominated by CCSNe and collapsar r-process nucleosynthesis. This conclusion may be testable if the next generation of observatories can deduce isotopic r-process abundances.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2004

Developing the JPL Engineering Processes

This paper briefly recounts the recent history of process reengineering at the NASA Jet Propulsion Laboratory, with a focus on the engineering processes. The JPL process structure is described and the process development activities of the past several years outlined. The main focus of the paper is on the current process structure, the emphasis on the flight project life cycle, the governance approach that lead to Flight Project Practices, and the remaining effort to capture process knowledge at the detail level of the work group.

reengineering↗

NASA NTRS2019

A Qualitative Investigation of Selected Infrared Flow Visualization Image Processing Techniques

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel testenvironment has resulted in a unique capability to image aerodynamic phenomena in real-time. Multi-camera infrared flow visualization data systems are now routinely utilized at the NASA Ames Unitary Plan Wind Tunnel. The small flow-induced temperature gradients on the surface of the wind tunnel test article coupled with the high bit-depth of the infrared camera sensor makes the processing of the image data critically important. An image processing routine must enhance features of interest with minimal artifacts. Additionally, the production wind tunnel test environment demands that these processed images are made available in a real-time, automatic fashion. Therefore, any image processing routine must be computationally economical and enhance the image data with minimal input from a human operator. The following seeks to qualitatively explore selected image processing techniques by assessing their effectiveness to resolve flow features on a wind tunnel test article. A multi-scale contrast enhancement technique is discussed as well as a new implementation of a multi-scale, non-interpolated adaptive histogram equalization. Finally, a novel method is introduced that demonstrates the ability to resolve flow features imaged on bare-steel test articles possessing low emissivity.This method makes use of dynamic mode decomposition and discrete-time filtering to separate the background reflections that dominate low emissivity surfaces from the aerodynamic driven surface temperature gradients.This process will be shown to resolve the onset of boundary layer transition on a bare metal wing as well as identify and resolve hidden features in the image data. While the implementation of this technique is very preliminary it demonstrates the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Image Processeing↗

NASA NTRSDate not supplied

Process Recipes for Additively Printed Copper Ink Flexible Circuits using Direct Write Methods

In this paper, the process-recipes and process-performance relationships for additive-printing of copper circuits using direct-write methods have been studied. The process has been implemented on the direct write platform. Interest in the use of additive printing methods for the manufacture of micro-circuits has grown immensely in recent times. Direct write methods have been shown to have the ability to create circuits in a limited manner. However, the process recipes and the effect of process parameters on the manufactured properties are not well understood. Copper ink is a good and cost-effective alternative to silver ink but its use has lagged owing to an increased propensity for oxidation. In this paper, photonic curing has been used to sinter copper ink to make the traces conductive. The method flashes high energy light that sinter metal particles instantaneously and the temperature of the substrate remains low. The effect of the different photonic sintering profiles on the mechanical and electrical properties of the printed traces has been studied in this paper.The print process parameters also play an important role in the line width and height that has been studied to print with the desired line profile for the end application. An LC filter circuit is been printed with SMD components been attached using an electrically conductive adhesive (ECA). The manufactured flexible LC filter is been tested for its frequency sweep to compare with the commercially available LC filer with the help of the Bode plot.

Process control↗