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Lessons from Earth Bioaerosol Sampling for Venus Habitability & Biosignature Science

Venus’s clouds are often discussed as a potential habitat. Several high-priority science goals – cloud aerosol composition, internal radiative flux, and aerosol residence time and circulation models – will improve our understanding of Venus in an astrobiology context. Lessons from Earth’s aerobiosphere can inform these requirements and interpretation of results. A stable Venus aerobiosphere would need microorganisms to reproduce faster than they settle out due to gravity. This is a joint constraint of the potential nutrients and energy influx, bioenergetic costs such as desiccation and radiation damage, and aerosol dynamics. Though life cycles involving S- and Fe-based redox metabolism have been proposed, at an optimistic estimate of 75% H2SO4, Venus aerosol water activity (aw) is still ~0.02, far below the observed microbial growth limit of ~0.6. Long-term desiccation with brief spurts of repair, growth and reproduction in response to transient water influx (perhaps volcanism) is the most likely model for Earth-like life on Venus – a ‘desert bloom’ scenario. In Earth’s troposphere, clouds can carry 103 – 105 cells/mL, some metabolically active. A better analogue may be Earth’s stratospheric sulfate aerosol layer: supercooled sulfuric acid aerosols (acid weight fraction 0.6 – 0.85, 0.1 – 1 µm diameter, 0.1 – 1 cm-3) with little water activity, long residence times, high UV radiation, and only sporadic influx from surface particle sources. Viable cells isolated from this region are rare (~102 cells/m3), though ‘hot spots’ at tropospheric mixing occur. Cells are primarily in inactive forms such as spores, and it is unclear if any are associated with sulfate aerosols or simply co-located. Given the heterogeneities in Venus clouds and the model of a sparse, largely dormant ecosystem, a single transect on descent would most likely pass through a low-water, inactive region, missing potential signs of habitability or biosignatures. Even a passive aerial platform (balloon) may end up following a single air mass over its lifetime. A better strategy for Venus would target an aerial region with some upwelling from surface sources, and take multiple transects separated in time and space. Earth’s stratospheric bioaerosol population could provide a starting point for estimating the required lower volume and detection limits.

Earth↗

DOE OSTI2016

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Background Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality based) version. Results In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

The pursuit of net-positive sustainability for industrial decarbonization with hybrid energy systems

We report signatories of the Paris Agreement are set to miss their climate targets. The net-zero pledges announced to date across many countries and private industries are insufficient to achieve carbon neutrality, which requires implementation of far-reaching and significantly scaled-up climate-positive actions. All technology options that pertain to deep decarbonization and carbon removal must be part of the mitigation portfolio. Transformative action plans must be established in which every individual/organization around the globe is an actor of changes in relation to net-zero goals. Such plans must involve governmental policy support but also encourage voluntary efforts to boost innovations, investments, initiatives, and behavioral changes. Recognition of these efforts is made quantifiable with the concepts of carbon handprint and net positivity. This paper presents a carbon handprint perspective on characterizing the environmental benefits of hybrid energy systems (HESs)—a widely applicable solution to cleaner production leveraging the capabilities of a portfolio of low-carbon energy sources—that provide heat and electricity to industrial processes. First, the carbon handprint and net positivity concepts and their calculation approach are introduced. The state of the art of HES-enabled industrial cogeneration is then surveyed, and the greenhouse gas emission intensities of different energy sources that power HESs are compared. Next, drawing on a case study about a US chemical facility's voluntary initiative to explore replacing its fossil fuel–based cogeneration infrastructure with a clean energy–generated HES, several technically viable scenarios are evaluated—especially those with small modular nuclear reactors—to illustrate how the positive-thinking handprint approach helps encourage and inform the search for widespread influence pathways in pursuit of net-positive sustainability. Finally, current knowledge gaps in the case study are identified, and opportunities to scale up the proposed handprint-based analysis are outlined with consideration of an expanded role of HESs in fulfilling climate objectives.It is envisioned that like-minded decision makers in the industry sector and beyond will adopt this perspective and act synergistically to enhance their environmental stewardship through voluntary actions and make greater contributions to the planet's climate future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗

DOE OSTI2024

The anomaly of the CMB power with the latest Planck data

Abstract The lack of power anomaly is an unexpected feature observed at large angular scales in the maps of Cosmic Microwave Background (CMB) produced by the COBE, WMAP andPlancksatellites. This signature, which consists in a missing of power with respect to that predicted by the ΛCDM model, might hint at a new cosmological phase before the standard inflationary era.The main point of this paper is taking into account the latestPlanckpolarisation data to investigate how the CMB polarisation improves the understanding of this feature. With this aim, we apply to the latestPlanckdata, both PR3 (2018) and PR4 (2020) releases, a new class of estimators capable of evaluating this anomaly by considering temperature and polarisation data both separately and in a jointly way. This is the first time that the PR4 dataset has been used to study this anomaly. To critically evaluate this feature, taking into account the residuals of known systematic effects present in thePlanckdatasets, we analyse the cleaned CMB maps using different combinations of sky masks, harmonic range and binning on the CMB multipoles.Our analysis shows that the estimator based only on temperature data confirms the presence of a lack of power with a lower-tail-probability (LTP), depending on the component separation method, ≤ 0.33% and ≤ 1.76% for PR3 and PR4, respectively. To our knowledge, the LTP≤ 0.33% for the PR3 dataset is the lowest one present in the literature obtained fromPlanck2018 data, considering thePlanckconfidence mask. We find significant differences between these two datasets when polarisation is taken into account most likely due to a different level of systematics. Especially, the analysis with PR3 data, unlike that with PR4, seems to point towards a lack of power at large scales also for polarisation.Moreover, we also show that for the PR3 dataset the inclusion of the subdominant polarisation information provides estimates that are less likely accepted in a ΛCDM cosmological model than the only-temperature analysis over the entire harmonic-range considered. In particular, at ℓ max = 26, we found that no simulation has a value as low as the data for all the pipelines.

Astronomy & Astrophysics↗

DOE OSTI2018

FUSRAP Case Study - Benefits and Lessons Learned from Implementation of a Modern Data Solution at Maywood - 18399

This paper focuses on data production and management practices dating back to 1999 that continue to evolve to support the project today. In 2000, the FUSRAP Maywood Project began using a software environmental data management system and laboratory information management system, developed by a single database administrator (DA) and authored in Microsoft Access{sup TM} (MS Access). The original databases included basic functionality including sample number assignment and label generation, tracking of LIMS gamma spec QC and assignment of basic qualifiers and basic database queries. The DA continued over the next fifteen years to refine the EDMS/LIMS by integrating project-specific data evaluation guidance document processes and Quality Assurance/Quality Control (QA/QC) charting and excursion warning tools. With the retirement of the original DA, the U.S. Army Corps of Engineers (USACE)-Cabrera Team procured and implemented a commercial-leaning solution using modern database tools and an established EDMS vendor. For the database transition process, the project team established and configured the new EDMS/LIMS with basic architecture and accessibility; evaluated existing workflows; established/revised LIMS and EDMS-related documentation (manuals and procedures); and conducted dry runs and validation testing. The overall team coordinated closely to facilitate a seamless transition from initial assessment and authoring, to data migration, and finally to resumption of normal ongoing operations. Key features of the new EDMS Subcontractor's software included lookup tables, an import wizard, data checking options and unique indexes. Since the database systems became operational, the technical staff gathered useful feedback from end users (e.g., lab staff, field engineers, task managers, and the third-party data validator) to refine the EDMS/LIMS operation. This feedback triggered improvements in the performance of onsite laboratory qualification forms, promoted consistency in sample ID numbers between the database sample planning screens and field chain-of-custodies, corrected bugs in the LIMS Duplicate Evaluation Report, eliminated data import issues such as blank, inconsistent or missing data from key fields. One of the advantages of the commercial database solution was that it allowed the project to cut cost over time due to the lower cost of database maintenance provided by the commercial database vendor versus the cost of an on-staff DA. Cost savings are estimated at $40,000 per year. There were also indirect cost savings resulting from implementation of the new database since it allowed better integration of the LIMS and EDMS. While there will always be challenges associated with long term records/data management for any old remediation site, the Maywood Team's approach to an upgraded EDMS/LIMS implementation serves as one element of the overall effort to enhance the integrity and reproducibility of critical data that supports the remediation program while at the same time, more effectively using available resources. These lessons-learned will enhance implementation of cost-effective solutions for similar environmental remediation sites. (authors)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

A cross-sectional study of the temporal evolution of electricity consumption of six commercial buildings

Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2006

Medical Operations Console Procedure Evaluation: BME Response to Crew Call Down for an Emergency

International Space Station (ISS) Mission Operations are managed by multiple flight control disciplines located at the lead Mission Control Center (MCC) at NASA-Johnson Space Center (JSC). ISS Medical Operations are supported by the complementary roles of Flight Surgeons (Surgeon) and Biomedical Engineer (BME) flight controllers. The Surgeon, a board certified physician, oversees all medical concerns of the crew and the BME provides operational and engineering support for Medical Operations Crew Health Care System. ISS Medical Operations is currently addressing the coordinated response to a crew call down for an emergent medical event, in particular when the BME is the only Medical Operations representative in MCC. In this case, the console procedure BME Response to Crew Call Down for an Emergency will be used. The procedure instructs the BME to contact a Surgeon as soon as possible, coordinate with other flight disciplines to establish a Private Medical Conference (PMC) for the crew and Surgeon, gather information from the crew if time permits, and provide Surgeon with pertinent console resources. It is paramount that this procedure is clearly written and easily navigated to assist the BME to respond consistently and efficiently. A total of five BME flight controllers participated in the study. Each BME participant sat in a simulated MCC environment at a console configured with resources specific to the BME MCC console and was presented with two scripted emergency call downs from an ISS crew member. Each participant used the procedure while interacting with analog MCC disciplines to respond to the crew call down. Audio and video recordings of the simulations were analyzed and each BME participant's actions were compared to the procedure. Structured debriefs were conducted at the conclusion of both simulations. The procedure was evaluated for its ability to elicit consistent responses from each BME participant. Trials were examined for deviations in procedure task completion and/or navigation, in particular the execution of the Surgeon call sequence. Debrief comments were used to analyze unclear procedural steps and to discern any discrepancies between the procedure and generally accepted BME actions. The sequence followed by BME participants differed considerably from the sequence intended by the procedure. Common deviations included the call sequence used to contact Surgeon, the content of BME and crew interaction and the gathering of pertinent console resources. Differing perceptions of task priority and imprecise language seem to have caused multiple deviations from the procedure s intended sequence. The study generated 40 recommendations for the procedure, of which 34 are being implemented. These recommendations address improving the clarity of the instructions, identifying training considerations, expediting Surgeon contact, improving cues for anticipated flight control team communication and identifying missing console tools.

Johnson-Troop↗

DOE OSTI2015

Bench-scale Development of an Advanced Solid Sorbent-based CO 2 Capture Process for Coal-fired Power Plants

It is increasingly clear that CO 2 capture and sequestration (CCS) must play a critical role in curbing worldwide CO 2 emissions to the atmosphere. Development of these technologies to cost-effectively remove CO 2 from coal-fired power plants is very important to mitigating the impact these power plants have within the world’s power generation portfolio. Currently, conventional CO 2 capture technologies, such as aqueous-monoethanolamine based solvent systems, are prohibitively expensive and if implemented could result in a 75 to 100% increase in the cost of electricity for consumers worldwide. Solid sorbent CO 2 capture processes – such as RTI’s Advanced Solid Sorbent CO 2 , Capture Process – are promising alternatives to conventional, liquid solvents. Supported amine sorbents – of the nature RTI has developed – are particularly attractive due to their high CO 2 loadings, low heat capacities, reduced corrosivity/volatility and the potential to reduce the regeneration energy needed to carry out CO 2 capture. Previous work in this area has failed to adequately address various technology challenges such as sorbent stability and regenerability, sorbent scale-up, improved physical strength and attrition-resistance, proper heat management and temperature control, proper solids handling and circulation control, as well as the proper coupling of process engineering advancements that are tailored for a promising sorbent technology. The remaining challenges for these sorbent processes have provided the framework for the project team’s research and development and target for advancing the technology beyond lab- and bench-scale testing. Under a cooperative agreement with the US Department of Energy, and part of NETL’s CO 2 Capture Program, RTI has led an effort to address and mitigate the challenges associated with solid sorbent CO 2 capture. The overall objective of this project was to mitigate the technical and economic risks associated with the scale-up of solid sorbent-based CO 2 capture processes, enabling subsequent larger pilot demonstrations and ultimately commercial deployment. An integrated development approach has been a key focus of this project in which process development, sorbent development, and economic analyses have informed each of the other development processes. Development efforts have focused on improving the performance stability of sorbent candidates, refining process engineering and design, and evaluating the viability of the technology through detailed economic analyses. Sorbent advancements have led to a next generation, commercially-viable CO 2 capture sorbent exhibiting performance stability in various gas environments and a physically strong fluidizable form. The team has reduced sorbent production costs and optimized the production process and scale-up of PEI-impregnated, fluidizable sorbents. Refinement of the process engineering and design, as well as the construction and operation of a bench-scale research unit has demonstrated promising CO 2 capture performance under simulated coal-fired flue gas conditions. Parametric testing has shown how CO 2 capture performance is impacted by changing process variables, such as Adsorber temperature, Regenerator temperature, superficial flue gas velocity, solids circulation rate, CO 2 partial pressure in the Regenerator, and many others. Long-term testing has generated data for the project team to set the process conditions needed to operate a solids-based system for optimal performance, with continuous 90% CO 2 capture, and no operational interruptions. Data collected from all phases of testing has been used to develop a detailed techno-economic assessment of RTI’s technology. These detailed analyses show that RTI’s technology has significant economic advantages over current amine scrubbing and potential to achieve the DOE’s Carbon Capture Program’s goal of >90% CO 2 capture rate at a cost of < $40/T-CO 2 captured by 2025. Through this integrated technology development approach, the project team has advanced RTI’s CO 2 capture technology to TRL-4 (nearly TRL-5, with the missing variable being testing on actual, coal-fired flue gas), according to the DOE/FE definitions for Technology Readiness Levels. At a broader level, this project has advanced the whole of the solid sorbent CO 2 capture field, with advancements in process engineering and design, technical risk mitigation, sorbent scale-up optimization, and an understanding of the commercial viability and applicability of solid sorbent CO 2 capture technologies for the U.S. existing fleet of coal-fired power plants.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2020

Assessment of NO2 Observations During DISCOVER-AQ and KORUS-AQ Field Campaigns

NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated data sets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a actor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori pro-files) but mostly to OMI’s large footprint (>312 km2).

Nitrogen dioxide↗

NASA NTRS2019

Energetic Particles of Cosmic Accelerators II: Active Galactic Nuclei and Gamma-ray Bursts

The high-energy universe has revealed that energetic particles are ubiquitous in the cosmos and play a vital role in the cultivation of cosmic environments on all scales. Our pursuit of more than a century to uncover the origins and fate of these cosmic energetic particles has given rise to some of the most interesting and challenging questions in astrophysics. Within our own galaxy, we have seen that energetic particles engage in a complex interplay with the galactic environment and even drive many of its key characteristics (for more information, see the first white paper in this series). On cosmological scales, the energetic particles supplied by the jets of active galactic nuclei (AGN) are an important source of energy for the intracluster and intergalactic media, providing a mechanism for regulating star formation and black hole growth and cultivating galaxy evolution (AGN feedback). Gamma-ray burst (GRB) afterglows encode information about their circumburst environment, which has implications for massive stellar winds during previous epochs over the stellar lifecycle. As such, GRB afterglows provide a means for studying very high-redshift galaxies since GRBs can be detected even if their host galaxy cannot. It has even been suggest that GRB could be used to measure cosmological distance scales if they could be shown to be standard candles. Though they play a key role in cultivating the cosmological environment and/or enabling our studies of it, there is still much we do not know about AGNs and GRBs, particularly the avenue in which and through which they supply radiation and energetic particles, namely their jets. Despite the enormous progress in particle-in-cell and magnetohydrodynamic simulations, we have yet to pinpoint the processes involved in jet formation and collimation and the conditions under which they can occur. For that matter, we have yet to identify the mechanism(s) through which the jet accelerates energetic particles – is it the commonly invoked diffusive shock acceleration process or is another mechanism, such as magnetic reconnection, required? Do AGNs and GRBs accelerate hadrons, and if so, do they accelerate them to ultra-high energies and are there high-energy neutrinos associated with them? MeV gamma-ray astronomy, enabled by technological advances that will be realized in the coming decade, will provide a unique and indispensable perspective on the persistent mysteries of the energetic universe. This White Paper is the second of a two-part series highlighting the most well-known high-energy cosmic accelerators and contributions that MeV gamma-ray astronomy will bring to understanding their energetic particle phenomena. Specifically, MeV astronomy will: 1. Determine whether AGNs accelerate CRs to ultra-high energies; 2. Provide the missing pieces for the physics of the GRB prompt emission; 3. Measure magnetization in cosmic accelerators and search for acceleration via reconnection.

Venters, Tonia M.↗

DOE OSTI2014

Review of Quantitative Monitoring Methodologies for Emissions Verification and Accounting for Carbon Dioxide Capture and Storage for California’s Greenhouse Gas Cap-and-Trade and Low-Carbon Fuel Standard Programs

The Cap-and-Trade and Low Carbon Fuel Standard (LCFS) programs being administered by the California Air Resources Board (CARB) include Carbon Dioxide Capture and Storage (CCS) as a potential means to reduce greenhouse gas (GHG) emissions. However, there is currently no universal standard approach that quantifies GHG emissions reductions for CCS and that is suitable for the quantitative needs of the Cap-and-Trade and LCFS programs. CCS involves emissions related to the capture (e.g., arising from increased energy needed to separate carbon dioxide (CO 2 ) from a flue gas and compress it for transport), transport (e.g., by pipeline), and storage of CO 2 (e.g., due to leakage to the atmosphere from geologic CO 2 storage sites). In this project, we reviewed and compared monitoring, verification, and accounting (MVA) protocols for CCS from around the world by focusing on protocols specific to the geologic storage part of CCS. In addition to presenting the review of these protocols, we highlight in this report those storage-related MVA protocols that we believe are particularly appropriate for CCS in California. We find that none of the existing protocols is completely appropriate for California, but various elements of all of them could be adopted and/or augmented to develop a rigorous, defensible, and practical surface leakage MVA protocol for California. The key features of a suitable surface leakage MVA plan for California are that it: (1) informs and validates the leakage risk assessment, (2) specifies use of the most effective monitoring strategies while still being flexible enough to accommodate special or site-specific conditions, (3) quantifies stored CO 2 , and (4) offers defensible estimates of uncertainty in monitored properties. California’s surface leakage MVA protocol needs to be applicable to the main CO 2 storage opportunities (in California and in other states with entities participating in California’s Cap-and-Trade or LCFS programs), specifically CO 2 -enhanced oil recovery (CO 2 -EOR), CO 2 injection into depleted gas reservoirs (with or without CO 2 -enhanced gas recovery (CO 2 -EGR)), as well as deep saline storage. Regarding the elements of an effective surface leakage MVA protocol, our recommendations for California are that: (1) both CO 2 and methane (CH 4 ) surface leakage should be monitored, especially for enhanced recovery scenarios, (2) emissions from all sources not directly related to injection and geologic storage (e.g., from capture, or pipeline transport) should be monitored and reported under a plan separate from the surface leakage MVA plan that is included as another component of the quantification methodology (QM), (3) the primary objective of the surface leakage MVA plan should be to quantify surface leakage of CO 2 and CH 4 and its uncertainty, with consideration of best-practices and state-of-the-art approaches to monitoring including attribution assessment, (4) effort should be made to monitor CO 2 storage and migration in the subsurface to anticipate future surface leakage monitoring needs, (5) detailed descriptions of specific monitoring technologies and approaches should be provided in the MVA plan, (6) the main purpose of the CO 2 injection project (CO 2 -EOR, CO 2 -EGR, or pure geologic carbon sequestration (GCS)) needs to be stated up front, (7) approaches to dealing with missing data and quantifying uncertainty need to be described, and (8) post-injection monitoring should go on for a period consistent with or longer than that prescribed by the U.S. EPA.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Digital Particle Image Velocimetry (DPIV) Used for Space-Time Correlations in Nozzle Flow

An optical measurement technique known as Digital Particle Image Velocimetry (DPIV) was used previously to characterize the first- and second-order statistical properties of both cold and hot jet flows from externally mixed nozzles in NASA Glenn Research Center's Nozzle Acoustic Test Rig. In this technique, an electronic camera records particles entrained in a flow as a laser light sheet is pulsed at two instances in time. Correlation processing of the recorded particle image pairs yields the two-component velocity field across the imaged plane of the flow. The information acquired using DPIV is being used to improve our understanding of the decay of turbulence in jet flows-a critical element for understanding the acoustic properties of the flow. Recently, two independent DPIV systems were installed in Glenn's Small Hot Jet Acoustic Rig, enabling multiplane correlations in time and space. The data were collected over a range of different Mach numbers and temperature ratios. DPIV system 1 was fixed to a large traverse rig, and DPIV system 2 was mounted on a small traverse system mounted on the large traverse frame. The light sheets from the two DPIV systems were aligned to lie in the same axial plane, with DPIV system 2 being independently traversed downstream along the flow direction. For each measurement condition, the DPIV systems were started at a fully overlapping orientation. A polarization separation technique was used to avoid cross-talk between the two systems. Then, the DPIV systems fields were shifted axially apart, in successively increasing steps. The downstream DPIV system 2 was triggered at a short time delay after the upstream DPIV system 1, where the time delay was proportional to the convective flow velocity in the shear layer of the jet flow and the axial separation of the two DPIV systems. The acquired data were processed to obtain the instantaneous velocity vector maps over a range of time delays and spatial separations. The velocity fields from the different DPIV systems were then cross-correlated to determine the degree of correlation remaining in the flow as the downstream convection distance was increased. The new data provide Lagrangian measurements of the convective turbulent structures in the shear layer of an exhaust nozzle. These measurements, obtained in both cold and hot flows, will be used to validate and correct models for space-time velocity correlations-long a missing key to predicting jet noise.

Wernet, Mark P.↗

NASA NTRSDate not supplied

Dynamics of A Vibration Isolation System Including Inertia of the Human Body

Using an exercise device in a spacecraft is liable to transmit an unacceptable amount of vibration to that vehicle. This is commonly mitigated by a Vibration Isolation System (VIS), whose dynamics must be analyzed to confirm that the oscillatory forces on the spacecraft remain within allowed range, both from a structural and microgravity perspective (see, e.g., [1]). When modeling a VIS for countermeasures devices, one common approach is to record forces and moments applied on the floor while exercising, and then drive the VIS simulation by applying these recorded loads to the exercise platform part of the VIS mechanical model. This approach misses the fact that when exercising on a moving platform, the force and moment on it will differ from that on the stationary floor due to inertial effects involving the human body. For example, standing up on a platform as it gives under the subject’s feet reduces the foot force on it, and such inertial effects are especially complex for rotational motion. In principle, one could model both the motion of the human body and dynamics of the VIS mechanism in a single combined simulation, e.g., employing a tool such as the commonly used biomechanical simulation OpenSim. Here, the joints of the human body would be driven kinematically along prescribed exercise trajectories while the dynamics engine computed the response of the VIS degrees of freedom. However, mechanism designers and biomechanics experts have their own established tools, making it very desirable to have a way of decoupling the biomechanics from the VIS modeling, simulation, and analyses. We have derived a set of equations that rigorously accomplishes this goal, and have implemented them as an interface function that provides an alternative driving mechanism for an existing force-based VIS analysis simulation. When enabled, the simulated human/VIS system dynamics is now driven by this function, instead of the recorded force methodology described above. The function is designed to accept input from a data file containing the required time-stamped human motion and inertia terms corresponding to the specific exercise in question. This data file is generated by an OpenSim plugin written for that purpose. The existing VIS analytical simulation is developed using NASA’s Trick Simulation Environment [2], as well as its MBDyn multibody dynamics [3] package. The presentation will provide a detailed overview of the mathematical formulation, assumptions, plugin implementation, software interfaces, and results for a sample set of representative exercises. The results from this work aim to better inform VIS design efforts, as well as countermeasure device/protocol designs with respect to exercise type and frequency effects on vehicle structural and microgravity restrictions.

Countermeasures↗

DOE OSTI2020

Oak Ridge National Laboratory Technical Input for the Nuclear Regulatory Commission Review of the 2017 Edition of ASME Section III, Division 5, ‘High Temperature Reactors’

To assist the Nuclear Regulatory Commission in its decision making on endorsement of the American Society for Mechanical Engineers Boiler and Pressure Vessel Code Section III, Division 5 (2017 Edition) for development of advanced non-light water reactors, the following Division 5 portions were reviewed: Article HBB-2000 Material; Article HCB-2000 Material; Article HGB-2000 Material; Mandatory Appendix HBB-I-14 Tables and Figures; and, Nonmandatory Appendix HBB-U Guidelines for Restricted Material Specifications to Improve Performance in Certain Service Applications. In addition to the 2017 Edition, the same parts of the 2019 Edition have also been reviewed as indicated in various sections of the report. This review was conducted by a collaboration of national laboratory and private sector participants with significant industrial experience, including some heavy lifting and deep diving from Clarus Consulting, LLC., all intended to achieve an objective, independent, and practical perspective. The report provides recommendations, descriptions of the evaluation methods, and the source references for the data used. To build confidence required for endorsement of the Code, this review was conducted as a verification and validation of the above Code contents. The objective of verification is to ensure that the Code is free of error – direct or implied; contains the information needed for its use, including proper coverage of the Code-specified materials for the intended application, and completeness and adequacy of references to other portions of the Code. The objective of validation is to authenticate that the Code tabulations and graphs represent design inputs consistent with what are determined using rules and methods specified by the Code. The authentication process used data that were assembled and/or generated independent of Code development, while the methods of analysis followed Code-specified methods where appropriate. The designated portions for this review cover the five alloys codified for high temperature reactor applications in Division 5, i.e. 316 SS, 304 SS, 800H, 2¼Cr-1Mo, and 9Cr-1Mo-V, regarding their general requirements, permitted specifications and design stress intensity values for pressure-retaining applications, deterioration in service, fatigue acceptance test, permissible weld materials, tensile and yield strength, expected minimum stress-to-rupture values (including for Alloy 718), weld stress rupture factors, permissible materials for bolting use, and restricted specifications in certain service applications. Additionally, stress intensity values for bolting materials including 316 SS, 304 SS and alloy 718 were reviewed. Analysis and discussion are also provided on contents outside of these designated Code portions where it was deemed relevant and necessary to develop a technically sound understanding of issues relating to the designated portions. Due to unavailability of sufficient test data on welds during the review period, the weld stress rupture factors in Tables HBB-I-10.14A to E, which cover a total of ten tables for the five alloys welded with twenty-eight different weld metals (some with similar properties), have been deferred to a future review effort. The review identified mainly two types of issues. The first type includes instances where the Code is found factually incomplete or incorrect, such as obsolete materials specifications listings, missing tabulation of stresses for bolting. Changes to the Code are recommended in these cases. The second type of issue includes instances where the Code tabulations and graphs are found to be less conservative than the review analysis results. In these cases, recommendations are made for further review and consideration where the difference in conservatism exceeds 10%, which is our threshold for questioning technical adequacy, meriting a risk assessment by the Nuclear Regulatory Commission and/or reactor designers. It is noted that this effort has been executed using all available data and established methods of analysis, including methods and criteria specified and used by the Code. As such, the findings that are presented in quantitative detail, in a format for convenient comparison with the Code, and with identification of where further review is recommended, should provide a sound technical basis for decisions about quantifying the implications of the reduced design margins and technical adequacy/inadequacy to form a basis for conditioning specific Code tabulation values on endorsement. Recommendations for specific changes to the Code, however, entail design conservatism considerations beyond the scope of this review effort, and are not made in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2007

Triaxial Probe Magnetic Data Analysis

The Triaxial Magnetic Moment Analysis software uses measured magnetic field test data to compute dipole and quadrupole moment information from a hardware element. It is used to support JPL projects needing magnetic control and an understanding of the spacecraft-generated magnetic fields. Evaluation of the magnetic moment of an object consists of three steps: acquisition, conditioning, and analysis. This version of existing software was extensively rewritten for easier data acquisition, data analysis, and report presentation, including immediate feedback to the test operator during data acquisition. While prior JPL computer codes provided the same data content, this program has a better graphic display including original data overlaid with reconstructed results to show goodness of fit accuracy and better appearance of the report graphic page. Data are acquired using three magnetometers and two rotations of the device under test. A clean acquisition user interface presents required numeric data and graphic summaries, and the analysis module yields the best fit (least squares) for the magnetic dipole and/or quadrupole moment of a device. The acquisition module allows the user to record multiple data sets, selecting the best data to analyze, and is repeated three times for each of the z-axial and y-axial rotations. In this update, the y-axial rotation starting position has been changed to an option, allowing either the x- or z-axis to point towards the magnetometer. The code has been rewritten to use three simultaneous axes of magnetic data (three probes), now using two "rotations" of the device under test rather than the previous three rotations, thus reducing handling activities on the device under test. The present version of the software gathers data in one-degree increments, which permits much better accuracy of the fit ted data than the coarser data acquisition of the prior software. The data-conditioning module provides a clean data set for the analysis module. For multiple measurements at a given degree, the first measurement is used. For omitted measurements, the missing field is estimated by linear interpolation between the two nearest measurements. The analysis module was rewritten for the dual rotation, triaxial probe measurement process and now has better moment estimation accuracy, based on the finer one degree of data acquisition resolution. The magnetic moments thus computed are used as an input to summarize the total spacecraft field.

Shultz, Kimberly↗

DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Advances in Cross-Cutting Ideas for Computational Climate Science

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.

54 ENVIRONMENTAL SCIENCES↗