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DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗

DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗

NASA NTRS2024

Exploring Standing and Reflected Slow-mode Waves in Flaring Coronal Loops: A Parametric Study Using 2.5D MHD Modeling

Abstract Recent observations of reflected propagating and standing slow-mode waves in hot flaring coronal loops have spurred our investigation into their underlying excitation and damping mechanisms. To understand these processes, we conduct 2.5D magnetohydrodynamic (MHD) simulations using an arcade active region model that includes a hot and dense loop. Our simulations allow for in-depth parametric investigations complementing and expanding our previous 3D MHD modeling results. We excite these waves using a large-amplitude, flow pulse applied at one footpoint of the loop in two distinct models as motivated by observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA). The first model (Model 1) incorporates classical compressive viscosity coefficient, while the second model (Model 2) adopts a 10-times enhanced viscosity coefficient. We obtain the following major results: (1) Our 2.5D MHD simulations reinforce previous conclusions derived from 1D and 3D MHD models that significantly enhanced viscosity is crucial for the rapid excitation of standing slow waves with damping times consistent with observations by Wang et al. (2015). (2)We uncover that nonlinearity in Model 1 delays the conversion of a reflected propagating wave into a standing wave. In contrast, Model 2 exhibits a much weak influence of nonlinearity on the excitation time of standing waves, thanks to the suppression of these effects by enhanced viscosity. (3) Our results reveal that the transverse temperature structure holds more influence on wave behavior than the density structure. In Model 1, increased loop temperature contrast significantly enhances wave trapping within the structure, mitigating the impact of temperature-dependent viscous damping. Conversely, in Model 2, the impact of temperature structure on wave behavior weakens in comparison to the effect of viscosity. (4) Model 1 displays evident nonlinear coupling to the fast and kink magnetoacoustic waves and pronounced wave leakage into the corona. Model 2 exhibits significantly weaker effects in this regard. Analyzing three observed wave events by SDO/AIA aligns with Model 2 predictions, providing further support for the substantial viscosity increase. Our 2.5D study unravels the complex interplay of wave-flow phenomena and nonlinear processes in coronal loops, extending our previous 1D modeling results to incorporate more realistic loop geometry. This provides insights into scenarios where 3D effects may be neglected, thereby enhancing our understanding of the intricate dynamics of the solar corona.

Tongjiang Wang↗

DOE OSTI2024

Setups for eliminating static charge of the ATLAS18 strip sensors

Abstract Construction of the new all-silicon Inner Tracker (ITk), developed by the ATLAS collaboration to beable to track charged particles produced at the High-Luminosity LHC, started in 2020 and is expected tocontinue till 2028. The ITk detector will include 18,000 highly segmented and radiation hard n+-in-psilicon strip sensors (ATLAS18), which are being manufactured by Hamamatsu Photonics. Mechanical and electrical characteristics of produced sensors are measured upon their delivery at several institutes participating in a complex Quality Control (QC) program. The QC tests performed on each individual sensor check the overall integrity and quality of the sensor.During the QC testing of ATLAS18 strip sensors, an increased number of sensors thatfailed the electrical tests was observed. In particular, IV measurements indicated an early breakdown,while large areas containing several tens or hundreds of neighbouring strips with low interstrip isolationwere identified by the Full strip tests, and leakage current instabilities were measured in a long-term leakage current stability setup. Moreover, a high surface electrostatic charge reaching a level of several hundreds of volts per inch was measured on a large number of sensors and on the plastic sheets, whichmechanically protect these sensors in their paper envelopes. Accumulated data indicates a clearcorrelation between observed electrical failures and the sensor charge-up.To mitigate the above-described issues, the QC testing sites significantly modified the sensor handlingprocedures and introduced sensor recovery techniques based on irradiation of the sensor surface with UVlight or application of intensive flows of ionized gas. In this presentation, we will describe the setupsimplemented by the QC testing sites to treat silicon strip sensors affected by static charge andevaluate the effectiveness of these setups in terms of improvement of the sensor performance.

Instruments & Instrumentation↗

DOE OSTI2020

Fabrication Lessons Learned of Transportation Packaging from the Perspective of a Design Authority - 20322

This paper presents lessons learned regarding fabricating packaging systems from the perspective of a design authority (DA). Capturing and implementing lessons learned is critical for an organization to reduce systematic project risk and thereby promote the likelihood of project success. This paper defines the design authority as the organization responsible for technical design, resolving technical design issues, quality assurance program, and maintenance of the packaging system license. A package system is defined as the packaging, its contents, and auxiliary equipment. Packages are certified by the NRC under 10 CFR 71[1] for transportation by ground. The following lessons learned subjects are presented in the paper: quality assurance, interpretation of drawing dimensional requirements, execution of manufacturing processes, hardware dimensional inspection, and leakage rate testing. All discrepancies presented in this paper have been resolved as described in the appropriate final data package. All described package systems are in compliance with their Safety Analysis Report (SAR) and certificate of conformance requirements. The intent of this paper is to identify opportunities for improving the outcome of future projects and to mitigate fabrication challenges proactively. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Assessment of Carbonated Brine Injection as Low-risk Strategy for Geologic Carbon Storage

The main objective of this early-phase research was to evaluate the techno-economic feasibility and risk associated with combined brine and CO 2 storage in SWD wells using brine dissolution in the North Dakota portion of the Williston Basin. Three simulation studies were conducted to investigate: (1) CO 2 phases at different conditions, (2) wellbore compatibility, and (3) long-term storage fate in reservoir. (1) A simple reservoir model and injection simulations were created using data to represent the BEST (brine extraction and storage test) site, an operational SWD facility located near Watford City, North Dakota. The pressure evolution caused by CO 2 comingled in produced water injectate in a layer cake reservoir was then modeled while tracking aqueous CO 2 throughout the project. The salinity of the injection water, the salinity of the reservoir brine, and the amount of dissolved CO 2 comingled in the injection water were varied. (2) A wellbore corrosion model was performed using the CO 2 concentrations selected based on the reservoir modeling to examine the carbonated produced water impact on wellbore. (3) Reactive transport modeling was conducted with the optimal CO 2 concentration for this injection site to study the rock-fluid interactions and CO 2 fate in the reservoir. Results suggest that CO 2 dissolved in produced water can be injected without appreciably increasing subsurface pressure or leakage risks. Pressure buildup was found to vary with salinity but not with CO 2 mass fraction. Simulation results show that lower CO 2 percent mass fraction leads to a higher amount of CO 2 that can be dissolved at a higher injection salinity. Furthermore, the long-term goal of dissolution trapping in a traditional carbon storage project is accomplished from the start, mitigating risks associated with potential migration of buoyant CO 2 , so long as the reservoir pressure and temperature are used to determine the maximum mass fraction of the dissolved CO 2 .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis

Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.

36 MATERIALS SCIENCE↗

DOE OSTI2021

NRAP-Open-IAM Multisegmented Wellbore Reduced-Order Model

Geologic carbon storage is one of the promising strategies to mitigate climate change by reducing the emission of carbon dioxide to the atmosphere. As part of the National Risk Assessment Partnership (NRAP), a systems-level stochastic analysis tool called the open source integrated assessment model, NRAP-Open-IAM, has been developed to estimate and manage the risk of containment loss at a geological carbon sequestration site. NRAP-Open-IAM contains several wellbore leakage model components that estimate the fluid leak rate that may occur through compromised legacy wells due to the increase in pressure resulting from CO 2 injection activities. Coupled to a reservoir component model, these components estimate the leakage of CO 2 and/or brine from a storage reservoir to overlying aquifer layers and the atmosphere through legacy wells. This report presents the theoretical framework and quality testing of the multisegmented wellbore reduced-order model. The model allows for segmenting of the legacy wells passing through the overlying stratigraphy into several intervals to simulate a site’s specific stratigraphic and hydrogeologic properties. For quality assurance, the analytical model is validated against numerical reservoir flow simulations for single and multiple aquifer(s) models. The results indicate that the model accurately predicts the transport of two-phase fluids (brine and injected CO 2 ) through the well over time. A detailed description of the model helps users to understand the model and provides a basis for future improvements.

58 GEOSCIENCES↗

NASA NTRS1999

SRAM Based Re-programmable FPGA for Space Applications

An SRAM (static random access memory)-based reprogrammable FPGA (field programmable gate array) is investigated for space applications. A new commercial prototype, named the RS family, was used as an example for the investigation. The device is fabricated in a 0.25 micrometers CMOS technology. Its architecture is reviewed to provide a better understanding of the impact of single event upset (SEU) on the device during operation. The SEU effect of different memories available on the device is evaluated. Heavy ion test data and SPICE simulations are used integrally to extract the threshold LET (linear energy transfer). Together with the saturation cross-section measurement from the layout, a rate prediction is done on each memory type. The SEU in the configuration SRAM is identified as the dominant failure mode and is discussed in detail. The single event transient error in combinational logic is also investigated and simulated by SPICE. SEU mitigation by hardening the memories and employing EDAC (error detection and correction) at the device level are presented. For the configuration SRAM (CSRAM) cell, the trade-off between resistor de-coupling and redundancy hardening techniques are investigated with interesting results. Preliminary heavy ion test data show no sign of SEL (single event latch-up). With regard to ionizing radiation effects, the increase in static leakage current (static I(sub CC)) measured indicates a device tolerance of approximately 50krad(Si).

Wang, J. J.↗

DOE OSTI2023

Concurrent characterization of GaN MOSHEMT gate leakage via electrical and thermoreflectance measurements

In this work, we report the first concurrent use of electrical and thermal characterization, via thermoreflectance, to analyze Time Dependent Dielectric Breakdown in GaN MOSHEMTs. Electrically stressing the devices until a failure occurs, then evaluating them via thermoreflectance, revealed a geometric dependence of the failure mode. Further, all soft breakdowns occurred at the mesa edge where the electric field strength was at its strongest, and tunneling current density was at its highest. This breakdown phenomenon at the mesa edge has been seen previously in GaN HEMTs employing a mesa architecture. Possible approaches to mitigate these failures in MOSHEMTs are proposed.

42 ENGINEERING↗

DOE OSTI2022

Improving Effective Mass Estimations in Pu-Metal Annuli

Determining the effective mass of 240 Pu in a plutonium metal item can be achieved through a number of destructive and non-destructive assay techniques. However, these techniques have one or more shortcomings. These include the need for large quantities of plutonium, long measurement time, or lack of sufficient accuracy. While efforts have been made to mitigate these issues by estimating 240 Pu quantities through neutron coincidence counting techniques, these estimates are subject to systematic bias, and their estimates are not well characterized when other factors of the annulus’ physical form and composition are accounted for. In this work, we expand upon these non-destructive assay techniques via the implementation of random forest machine learning models, which produce correction functions that augment and improve the effective mass estimates derived from classical leakage multiplication, singles, doubles, and triples multiplicity counting equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Mitigating electrochemical degradation in CsPbBr{sub 3} gamma detectors by organic and inorganic encapsulation.

CsPbBr3 perovskite semiconductors have emerged as a leading candidate for nextgeneration radiation detectors because of their exceptional charge transport properties, defect tolerance, and record-breaking sensitivity and energy resolution. Their long-term stability, however, is hindered by electrode-driven electrochemical decomposition, which is accelerated by moisture- and oxygen-assisted ion migration during operation. Here, we investigated organic and inorganic encapsulation strategies as both environmental barriers and means to suppress interfacial degradation pathways. Atomic layer deposition (ALD) of Al2O3 provided a conformal passivation layer that blocked environmental ingress, suppressed ionic diffusion, reduced leakage current, enhanced energy resolution and expanded the operational electric-field window beyond 5 kV∙cm1 . By contrast, organic encapsulants such as paraffin wax and polystyrene slowed moisture diffusion but did not suppress interfacial reactions, with wax extending stability to over 90 days. These results show that ALD-Al2O3 suppresses dominant interfacial degradation pathways, enabling stable, high-field operation and advancing the practical deployment of CsPbBr3 γ-ray detectors.

Unal, Mustafa↗

NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗

NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

Brian R. Richardson↗

NASA NTRS2015

Anti-Adhesion Elastomer Seal Coatings for Ultraviolet and Atomic Oxygen Protection

Radiation blocking sunscreen coatings have been developed for the protection of elastomer seals used in low-Earth-orbit (LEO). The coatings protect the seals from ultraviolet (UV) radiation and atomic oxygen (AO) damage. The coatings were developed for use on NASA docking seals. Docking seal damage from the UV and AO present in LEO can constrain mission time-line, flight mode options, and increases risk. A low level of adhesion is also required for docking seals so undocking push-off forces can be low. The coatings presented also mitigate this unwanted adhesion. Greases with low collected volatile condensable materials (CVCM) and low total mass loss (TML) were mixed with slippery and/or UV blocking powders to create the protective coatings. Coatings were applied at rates up to 2 milligrams per square centimeter. Coated seals were exposed to AO and UV in the NUV (near-UV) and UV-C wavelength ranges (300 to 400 nanometers and 254 nanometers, respectively). Ground based ashers were used to simulate the AO of space. The Sun's UV energy was mimicked assuming a nose forward flight mode, resulting in an exposure rate of 2.5 megajoules per square meter per day. Exposures between 0 and 147 megajoules per square meter (UV-C) and 245 megajoules per square meter (NUV) were accomplished. The protective coatings were durable, providing protection from UV after a simulated docking and undocking cycle. The level of protection begins to decline at coverage rates less than 0.9 milligrams per square centimeter. The leakage of seals coated with Braycote plus 20 percent Z-cote ZnO sunscreen increased by a factor of 40 after moderate AO exposure; indicating that this coating might not be suitable due to AO intolerance. Seals coated with DC-7-16.4 percent Z-cote ZnO sunscreen were not significantly affected by combined doses of 2 x 10 (sup 21) atoms per square AO with 73 megajoules per square meter UV-C. Unprotected seals were significantly damaged at UV-C exposures of 0.3 megajoules per square meter and DC-7-16.4 percent Z-cote coated seals were undamaged at all exposures up to the limits tested thus far which were 147 megajoules per square meter UV-C and 245 megajoules per square meter NUV. The coatings decreased adhesion sufficiently for docking seals at temperatures equal to or greater than -8 degrees Centigrade thus offer a simple and inexpensive way to mitigate adhesion.

adhesion↗

DOE OSTI2022

Two-Phase Flow Mechanisms Controlling CO2 Intrusion into Shaly Caprock

Abstract Geologic carbon storage in deep saline aquifers has emerged as a promising technique to mitigate climate change. CO 2 is buoyant at the storage conditions and tends to float over the resident brine jeopardizing long-term containment goals. Therefore, the caprock sealing capacity is of great importance and requires detailed assessment. We perform supercritical CO 2 injection experiments on shaly caprock samples (intact caprock and fault zone) under representative subsurface conditions. We numerically simulate the experiments, satisfactorily reproducing the observed evolution trends. Simulation results highlight the dynamics of CO 2 flow through the specimens with implications to CO 2 leakage risk assessment in field practices. The large injection-induced overpressure drives CO 2 in free phase into the caprock specimens. However, the relative permeability increase following the drainage path is insufficient to provoke an effective advancement of the free-phase CO 2 . As a result, the bulk CO 2 front becomes almost immobile. This implies that the caprock sealing capacity is unlikely to be compromised by a rapid capillary breakthrough and the injected CO 2 does not penetrate deep into the caprock. In the long term, the intrinsically slow molecular diffusion appears to dominate the migration of CO 2 dissolved into brine. Nonetheless, the inherently tortuous nature of shaly caprock further holds back the diffusive flow, favoring safe underground storage of CO 2 over geological time scales.

58 GEOSCIENCES↗