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Predicting the potential for mineral scale precipitation in unconventional reservoirs due to fluid-rock and fluid mixing geochemical reactions

Mineral precipitation within hydraulically fractured shale may affect fluid flow pathways and impact longterm hydrocarbon production. The ability to predict geochemical reactions that lead to problematic mineral precipitation will lead to active reservoir management strategies to improve overall production. Using the Marcellus Shale as a case study, a combination of laboratory experiments and reaction path modeling was applied to determine which reactions are likely to occur upon introduction of hydraulic fracturing fluid into the shale reservoir. Experimental results indicate that contact between fracturing fluid and shale will result in dissolution of primary minerals (quartz, feldspars, kaolinite, chlorite, pyrite) and secondary mineral precipitation over time periods of less than one week. Precipitation of barite, Fe-oxides, feldspars, amorphous silica and clay is likely to occur within the reservoir during shut in and early flowback due to mixing between fracturing fluid and reservoir brine as based on modeling saturation indices using experimental fluid data. Reaction path modeling of the experimental scenarios corroborates the specific dissolution and precipitation reactions observed experimentally. Comparison of the results to injected and produced waters from a Marcellus Shale well pad in Greene County, PA, USA, shows that the mineral reactions occur during the hydraulic fracturing, shut in, and early flowback periods. The results presented in this paper demonstrate the value in applying experimental approaches to identify mineral precipitation/dissolution reactions that may significantly impact reservoir performance. The good agreement between geochemical models and experimental results provides confidence that numerical models can be applied to screen the potential fluid-mineral and fluid-mixing reactions in unconventional reservoirs that result in undesired mineral scale precipitation.

58 GEOSCIENCES↗

Cross-code comparison of the impact of the fill tube on high yield implosions on the National Ignition Facility

Fill tubes are used to inject deuterium and tritium fuel into inertial confinement fusion capsules fielded on the National Ignition Facility. These fill tubes have been shown to have a detrimental effect on capsule performance, primarily by introducing a low-density pathway into the central fuel region that enables the jetting of ablation material into the hot spot. Due to the complexity of the highly nonlinear flow associated with the fill tube and the challenge of diagnosing the evolution of the fill tube jet late in the implosion experiments, the uncertainty in how this perturbation source evolves is great. In this work, we report on the results of a detailed code comparison performed to understand uncertainties in computational modeling of the impact of fill tubes on implosion performance. The study employed two radiation-hydrodynamics codes, HYDRA and xRAGE, which employ very different meshing strategies and hydrodynamics solvers, as well as two radiation transport methodologies, discrete ordinates and multi-group diffusion. Our results demonstrate generally good agreement between codes through most of the implosion although they indicate sensitivity to opacity averaging methods. Late in the implosion, differences arise in the distribution and amount of contaminant although these differences have a remarkably small impact on the amount of yield reduction due to the fill tube. While these results demonstrate sensitivity in fill tube modeling to algorithmic choices, the observed differences between codes are small relative to known sensitivities due to expected variations in the fill tube geometry. Finally, we have developed a methodology for performing multi-group diffusion simulations that show good agreement with the more accurate discrete ordinates method

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Scalable fabrication of a tough and recyclable spore-bearing biocomposite thermoplastic polyurethane

Thermoplastic polyurethanes (TPUs) are a class of versatile thermoplastic elastomers, but most of their products lack a proper recycling strategy or have no end-of-life solutions. To pursue a sustainable end-of-life solution for TPU-based products, self-disintegrating biocomposite TPUs have recently been developed by embedding spores of TPU-degrading bacteria into TPUs via melt extrusion. Herein, we improve upon spore-bearing biocomposites and demonstrate industrially relevant manufacturing conditions for fabricating biocomposite TPUs. To minimize the coloration of biocomposite TPUs, spore production was modified. The innate brown color of the resulting materials was diminished by reducing FeSO 4 in sporulation media, generating white spores without compromising spore productivity, viability, morphology or heat-shock tolerance. Biocomposite TPUs containing white spores displayed a 45 % increase in toughness compared to TPUs without spores, while retaining ∼ 90 % spore viability post processing. Furthermore, biocomposite TPU fabrication was demonstrated using a scalable continuous extruder followed by injection molding. Biocomposite TPUs generated by these industry-relevant processes exhibited comparable toughness improvement and spore viability to biocomposite TPU prepared using a lab scale microcompounder, while enhancing productivity by 30-fold. Finally, spore addition significantly improved the recyclability of biocomposite TPUs, enabling 80 % toughness retention after 5 rounds of iterative melt processing. Additionally, no negative effect on the lifespan of the generated TPUs was observed over 1 year of storage. Overall, this study confirms that spore-bearing biocomposite TPUs are promising for practical applications, offering an accessible method to enhance toughness and sustainability of commercial TPUs through the incorporation of spore-based living fillers.

36 MATERIALS SCIENCE↗

Neuroprotectin D1 Attenuates Blast Overpressure Induced Reactive Microglial Cells in the Cochlea

Objective/Hypothesis We examined a neuroinflammatory response associated with glial activation in the cochlea exposed to blast overpressure and evaluated the potential therapeutic efficacy of specialized pro‐resolving mediators such as neuroprotectin D1, NPD1; (10R, 17S‐dihydroxy‐4Z, 7Z, 11E, 13E, 15Z, 19Z‐docosahexaenoic acid) in a rodent blast‐induced auditory injury model. Study Design Animal Research. Methods A compressed‐air driven shock tube was used to expose anesthetized adult male Long‐Evan rats to shock waves simulating an open‐field blast exposure. Approximately 30 minutes after blast exposure, rats were treated with NPD1 (100 ng/kg body wt.) or vehicle delivered intravenously via tail vein injection. Rats were then euthanized 48 hours after blast exposure. Unexposed rats were included as controls. Tissue sections containing both middle and inner ear were prepared with hematoxylin–eosin staining to elucidate histopathological changes associated with blast exposure. Cochlear tissues were evaluated for relative expression of ionized calcium‐binding adaptor 1 (Iba1), as an indicator of microglial activation by immunohistochemistry and western blot analyses. Results Our animal model resulted in an acute injury mechanism manifested by damage to the tympanic membrane, hemorrhage, infiltration of inflammatory cells, and increased expression of Iba1 protein. Moreover, therapeutic intervention with NPD1 significantly reduced Iba1 expression in the cochlea, suggesting a reduction of a neuroinflammatory response caused by blast overpressure. Conclusions Blast overpressure resulted in an increased expression of proteins involved in gliosis within the auditory system, which were reduced by NPD1. Treatment of NPD1 suggests an effective strategy to reduce or halt auditory microglial cell activation due to primary blast exposure. Level of Evidence NA Laryngoscope , 131:E2018–E2025, 2021

Ríos, José David↗

Encapsulation of Monolayer 2D Materials Using Kinetic Energy-Controlled Pulsed Laser Deposition

The integration of monolayer (ML) two-dimensional (2D) materials into next-generation microelectronics, optoelectronics, and sensors is hindered by their sensitivity to environmental exposure. Deposition of additional layers for encapsulation or growth on ML 2D materials by versatile but energetic plasma techniques such as pulsed laser deposition (PLD) has not been considered at the monolayer level because of potential damage caused by hyperthermal species with kinetic energies (KEs) exceeding the threshold displacement energy (TDE) of the ML. Here, we describe a general strategy to understand and mitigate damage during PLD by reducing the incident KE of ablated species below the TDE of the 2D monolayer using background gas collisions. Ion flux diagnostics, combined with in situ Raman spectroscopy of monolayer graphene during PLD of amorphous boron nitride (a-BN) as a dielectric encapsulation layer, show that damage is primarily correlated with fast ions that penetrate the background gas in accordance with Beer’s Law and are often overlooked in ICCD imaging due to the dominance of the bright, delayed plasma luminescence. Significantly, if fast ions are eliminated and a ∼2 nm-thick a-BN layer is “soft landed”, the monolayer graphene is effectively protected from damage by high KE species in the boron nitride plasma plume. Deposited a-BN films display a characteristic dielectric constant of 3.6 at 100 kHz and tunable charge injection properties. Our results enable PLD as a viable option for encapsulation and thin film growth onto ML 2D materials, with implications for both fundamental research and device integration.

2D materials↗

Ambient Synthesis for Fe(II) Polypyridyl Complexes with an Order of Magnitude Increase in Charge-Transfer Excited-State Lifetimes over [Fe(bpy) 3 ] 2+

Replacing precious metals with abundant metals is an important research focus in photochemical energy conversion and storage to meet global energy demands. However, transition metal complexes (TMCs) based on abundant 3d metals typically possess photochemical disadvantages─such as short charge-transfer excited-state lifetimes─and molecular modifications have focused on optimizing the interplay of structure, dynamics, and energetics to overcome their limitations. One strategy to do so is the use of bespoke ligands that can extend the lifetimes of chemically useful excited states. Here, in this study, we report the synthesis and characterization of novel Fe(II) complexes featuring lengthy polypyridyl ligands that can be readily synthesized. Steady-state and transient absorption spectroscopies indicate that these complexes have desirable properties and their excited metal-to-ligand charge-transfer states live an order of magnitude longer than in the benchmark [Fe(bpy) 3 ] 2+ . This lifetime is largely preserved in the heteroleptic complexes, thereby enabling the preparation of asymmetric complexes. Additionally, we apply nonradiative transition theory to explain the long-time decay kinetics. In light of their ease of preparation and reasonable excited-state lifetimes, we suggest the use of these complexes in Fe(II) dye-sensitized solar cells, where the rate of charge injection would be competitive with increased lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In silico trials predict that combination strategies for enhancing vesicular stomatitis oncolytic virus are determined by tumor aggressivity

Background Immunotherapies, driven by immune-mediated antitumorigenicity, offer the potential for significant improvements to the treatment of multiple cancer types. Identifying therapeutic strategies that bolster antitumor immunity while limiting immune suppression is critical to selecting treatment combinations and schedules that offer durable therapeutic benefits. Combination oncolytic virus (OV) therapy, wherein complementary OVs are administered in succession, offer such promise, yet their translation from preclinical studies to clinical implementation is a major challenge. Overcoming this obstacle requires answering fundamental questions about how to effectively design and tailor schedules to provide the most benefit to patients. Methods We developed a computational biology model of combined oncolytic vaccinia (an enhancer virus) and vesicular stomatitis virus (VSV) calibrated to and validated against multiple data sources. We then optimized protocols in a cohort of heterogeneous virtual individuals by leveraging this model and our previously established in silico clinical trial platform. Results Enhancer multiplicity was shown to have little to no impact on the average response to therapy. However, the duration of the VSV injection lag was found to be determinant for survival outcomes. Importantly, through treatment individualization, we found that optimal combination schedules are closely linked to tumor aggressivity. We predicted that patients with aggressively growing tumors required a single enhancer followed by a VSV injection 1 day later, whereas a small subset of patients with the slowest growing tumors needed multiple enhancers followed by a longer VSV delay of 15 days, suggesting that intrinsic tumor growth rates could inform the segregation of patients into clinical trials and ultimately determine patient survival. These results were validated in entirely new cohorts of virtual individuals with aggressive or non-aggressive subtypes. Conclusions Based on our results, improved therapeutic schedules for combinations with enhancer OVs can be studied and implemented. Our results further underline the impact of interdisciplinary approaches to preclinical planning and the importance of computational approaches to drug discovery and development.

60 APPLIED LIFE SCIENCES↗

Colloidal Synthesis of Palladium Nanocluster‐Decorated Cs 3 Sb 2 Cl 9 Perovskite Heterostructural Nanorods for Enhanced CO 2 Photoreduction

Developing efficient and sustainable photocatalysts for CO 2 reduction remains a significant challenge, particularly with environmentally benign materials. Here, in this study, we report the first one-step synthesis of metal–lead-free perovskite heterostructural nanocrystals by decorating Cs 3 Sb 2 Cl 9 perovskite nanorods with size-controlled Pd nanoclusters via a one-step hot-injection method. The resulting Pd-Cs 3 Sb 2 Cl 9 heteronanorods (HNRs) exhibit strong interfacial electronic coupling, enhanced charge separation, and excellent colloidal stability. Transient absorption spectroscopy and DFT calculations reveal a built-in electric field that drives directional electron transfer from the perovskite host to the Pd domains. Under UV irradiation, the Pd-Cs 3 Sb 2 Cl 9 HNRs demonstrate excellent CO 2 photoreduction activity with high CH 4 selectivity, achieving a record apparent quantum yield (AQY) of 2.62% among halide perovskite nanocrystal-based systems with a large electronic yield of 689.3 ± 12.2 µmol·g cat −1 . In situ spectroscopic monitoring and Gibbs free energy analysis further unveil a Pd-facilitated reaction pathway involving stabilization of key intermediates. This work introduces a new class of lead-free perovskite-based heterostructures through a facile one-step synthesis strategy and offers a new design principle for next-generation photocatalysts for solar fuel production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗

A Theory of Oscillating Edge Flames

It has been known for some years that when a near-limit flame spreads over a liquid pool of fuel, the edge of the flame can oscillate relative to a frame moving with the mean speed. Each period of oscillation is characterized by long intervals of modest motion during which the edge gases radiate like those of a diffusion flame, punctuated by bursts of rapid advance during which the edge gases radiate like those in a deflagration. Substantial resources have been brought to bear on this issue within the microgravity program, both experimental and numerical. It is also known that when a near-asphyxiated candle-flame burns at zero gravity, the edge of the (hemispherical) flame can oscillate violently prior to extinction. Thus a web-surfer, turning to the NASA web-site at http://microgravity.msfc.nasa.gov, and following the trail combustion science/experiments/experimental results/candle flame, will find photographs and a description of candle burning experiments carried out on board both the Space-shuttle and the Russian space station Mir. A brief report can also be found in the proceedings of the Fourth Workshop. And recently, in a third microgravity program, the leading edge of the flame supported by injection of ethane through the porous surface of a plate over which air is blown has been found to oscillate when conditions are close to blow-off. A number of important points can be made with respect to these observations: It is the edge itself which oscillates, advancing and retreating, not the diffusion flame that trails behind the edge; oscillations only occur under near limit conditions; in each case the Lewis number of the fuel is significantly larger than 1; and because of the edge curvature, the heat losses from the reacting edge structure are larger than those from the trailing diffusion flame. We propose a general theory for these oscillations, invoking Occam's 'Law of Parsimony' in an expanded form, to wit: The same mechanism is responsible for the oscillations in all three experiments; and no new mechanism is invoked (Occam's original 'Razor'). Such a strategy eliminates Marangoni effects as the source, for these are absent in the second and third experiments. And it eliminates arguments that point to numerically predicted gas eddies as the source, a new mechanism, unelucidated. Indeed, we hypothesize that the essential driving mechanism for the instability is a combination of large Lewis number and heat losses from the reacting structure near the flame edge. Instabilities driven by these mechanisms are commonplace in 1D configurations. Chemical reactor theory, for example, leads to system responses which mimic the response of the candle flame - steady flame, oscillations, extinction. In a combustion context, oscillating instabilities were first reported for diffusion flames in a theoretical study by Kirkby and Schmitz, and here also the instabilities are associated with near-extinction conditions, large Lewis numbers, and heat losses. And deflagrations will oscillate if the Lewis number is large enough, oscillations that are exacerbated when heat losses are present, whether global or to a surface.

Buckmaster, J.↗

Changes in Hadley circulation and intertropical convergence zone under strategic stratospheric aerosol geoengineering

Stratospheric aerosol geoengineering has been proposed as a potential solution to reduce climate change and its impacts. Here, we explore the responses of the Hadley circulation (HC) intensity and the intertropical convergence zone (ITCZ) using the strategic stratospheric aerosol geoengineering, in which sulfur dioxide was injected into the stratosphere at four different locations to maintain the global-mean surface temperature and the interhemispheric and equator-to-pole temperature gradients at present-day values (baseline). Simulations show that, relative to the baseline, strategic stratospheric aerosol geoengineering generally maintains northern winter December–January–February (DJF) HC intensity under RCP8.5, while it overcompensates for the greenhouse gas (GHG)-forced southern winter June–July–August (JJA) HC intensity increase, producing a 3.5 ± 0.4% weakening. The residual change of southern HC intensity in JJA is mainly associated with stratospheric heating and tropospheric temperature response due to enhanced stratospheric aerosol concentrations. Geoengineering overcompensates for the GHG-driven northward ITCZ shifts, producing 0.7° ± 0.1° and 0.2° ± 0.1° latitude southward migrations in JJA and DJF, respectively relative to the baseline. These migrations are affected by tropical interhemispheric temperature differences both at the surface and in the free troposphere. Further strategies for reducing the residual change of HC intensity and ITCZ shifts under stratospheric aerosol geoengineering could involve minimizing stratospheric heating and restoring and preserving the present-day tropical tropospheric interhemispheric temperature differences.

54 ENVIRONMENTAL SCIENCES↗

A distributed voltage inference framework for cyber-physical attacks detection and localization in active distribution grids

The transition to active distribution grids with real-time monitoring and control depends on the proliferation of advanced communication networks and devices. This paradigm shift towards a cyber-physical architecture also introduces new vulnerabilities for adversaries to exploit and launch sophisticated cyber-physical attacks targeting grid observability. Current research highlights the challenges in distinguishing attacks on voltage phasor or nodal injection measurements and isolating multi-source attack locations in a multiphase distribution grid. The attack detection and localization methods in literature face accuracy issues, applications across diverse attack scenarios, or scalability limits. Here, to bridge these gaps, this paper proposes a distributed Voltage Inference framework for real-time detection and localization of cyber-physical attacks, addressing scalability, adaptability, and accuracy challenges in state-of-the-art methods. The proposed methodology leverages the distributed nature of the Voltage Inference framework through a two-step process of prediction and correction, together with a tractable graph partitioning approach, providing a reliable solution to identify compromised measurement sources and facilitate isolation. Extensive testing on IEEE 13 and 123-node distribution feeders underscores the algorithm’s efficacy, enhancing the security and resilience of active distribution grids against evolving cyber threats. Additionally, Hardware-in-the-Loop (HIL) implementation validates the proposed strategy’s practical applicability in real-world scenarios.

active distribution grids↗

Preferential Direction of Electron Transfers at a Dye–Metal Oxide Interface with an Insulating Fluorinated Self-Assembled Monolayer and MgO

Slowing non-desirable electron transfer reactions at metal oxide-dye interfaces is important for many technologies. Specifically, after an interfacial photoinduced charge separation event at a metal oxide-dye interface, it is critically important to limit the rate of electron transfer reactions back to sensitizers and to limit electron transfer reactions between the electrolyte and the metal oxide. Ruthenium-based dyes at metal oxide interfaces are widely used in many fields; however, these dyes often have poor surface insulation resulting in fast recombination kinetics with transition metal-based redox shuttles in an electrolyte. This work explores two semiconductor surface modification strategies designed to minimize recombination events of electrons in TiO 2 with oxidized redox shuttles using a fluorinated siloxane insulator (PFTS) and a metal oxide insulator (MgO) with a well-known Ru dye, B11. Additionally, the influence of these treatments on the rate and duration of photoinduced interfacial charge separation at the TiO 2 -dye interface was examined. The TiO 2 -dye-redox shuttle systems were studied via dye-sensitized solar cell current-voltage curve, incident photon-to-current conversion efficiency, small-modulated photovoltage transient, time-correlated single photon counting, and transient absorption spectroscopy measurements. MgO was found to decrease the rate of the electron transfer reaction from the metal oxide to the electrolyte, decrease the rate of the electron transfer reaction to the oxidized dye from TiO 2 , increase the electron transfer reaction rate from a reduced redox shuttle to an oxidized dye, and decrease the electron injection rate from the photoexcited dye to TiO2. Interestingly, PFTS was found to desirably improve on these rates relative to MgO or untreated TiO 2 . Here, a model based on electrostatic interactions is presented to explain the exceptional behavior of PFTS with DFT computational analysis of PFTS supporting this model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Launch and Assembly Reliability Analysis for Human Space Exploration Missions

NASA's future human space exploration strategy includes single and multi-launch missions to various destinations including cis-lunar space, near Earth objects such as asteroids, and ultimately Mars. Each campaign is being defined by Design Reference Missions (DRMs). Many of these missions are complex, requiring multiple launches and assembly of vehicles in orbit. Certain missions also have constrained departure windows to the destination. These factors raise concerns regarding the reliability of launching and assembling all required elements in time to support planned departure. This paper describes an integrated methodology for analyzing launch and assembly reliability in any single DRM or set of DRMs starting with flight hardware manufacturing and ending with final departure to the destination. A discrete event simulation is built for each DRM that includes the pertinent risk factors including, but not limited to: manufacturing completion; ground transportation; ground processing; launch countdown; ascent; rendezvous and docking, assembly, and orbital operations leading up to trans-destination-injection. Each reliability factor can be selectively activated or deactivated so that the most critical risk factors can be identified. This enables NASA to prioritize mitigation actions so as to improve mission success.

Cates, Grant↗

HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model

Abstract. A new set of standalone parameterizations is presented for simulating the injection, evolution, and radiative forcing by stratospheric volcanic aerosols against an idealized Held–Suarez–Williamson (HSW) atmospheric background in the Energy Exascale Earth System Model version 2 (E3SMv2). In this model configuration (HSW with enabled volcanism, HSW-V), sulfur dioxide (SO2) and ash are injected into the atmosphere with a specified profile in the vertical, and they proceed to follow a simple exponential decay. The SO2 decay is modeled as a perfect conversion to a long-living sulfate aerosol which persists in the stratosphere. All three species are implemented as tracers in the model framework and are transported by the dynamical core's advection algorithm. The aerosols contribute simultaneously to local heating of the stratosphere and cooling of the surface by a simple plane-parallel Beer–Lambert law applied on two zonally symmetric radiation broadbands in the longwave and shortwave ranges. It is shown that the implementation parameters can be tuned to produce realistic temperature anomaly signatures of large volcanic events. In particular, results are shown for an ensemble of runs that mimic the volcanic eruption of Mt. Pinatubo in 1991. The design requires no coupling to microphysical subgrid-scale parameterizations and thus approaches the computational affordability of prescribed aerosol forcing strategies. The idealized simulations contain a single isolated volcanic event against a statistically uniform climate, where no background aerosols or other sources of externally forced variability are present. HSW-V represents a simpler-to-understand tool for the development of climate source-to-impact attribution methods.

Hollowed, Joseph P. (ORCID:0000000286581672)↗

Two cis elements collaborate to spatially repress transcription from a sea urchin promoter

The expression pattern of many territory-specific genes in metazoan embryos is maintained by an active process of negative spatial regulation. However, the mechanism of this strategy of gene regulation is not well understood in any system. Here we show that reporter constructs containing regulatory sequence for the SM30-alpha gene of Stronglyocentrotus purpuratus are expressed in a pattern congruent with that of the endogenous SM30 gene(s), largely as a result of active transcriptional repression in cell lineages in which the gene is not normally expressed. Chloramphenicol acetyl transferase assays of deletion constructs from the 2600-bp upstream region showed that repressive elements were present in the region from -1628 to -300. In situ hybridization analysis showed that the spatial fidelity of expression was severely compromised when the region from -1628 to -300 was deleted. Two highly repetitive sequence motifs, (G/A/C)CCCCT and (T/C)(T/A/C)CTTTT(T/A/C), are present in the -1628 to -300 region. Representatives of these elements were analyzed by gel mobility shift experiments and were found to interact specifically with protein in crude nuclear extracts. When oligonucleotides containing either sequence element were co-injected with a correctly regulated reporter as potential competitors, the reporter was expressed in inappropriate cells. When composite oligonucleotides, containing both sequence elements, were fused to a misregulated reporter, the expression of the reporter in inappropriate cells was suppressed. Comparison of composite oligonucleotides with oligonucleotides containing single constituent elements show that both sequence elements are required for effective spatial regulation. Thus, both individual elements are required, but only a composite element containing both elements is sufficient to function as a tissue-specific repressive element.

Non-NASA Center↗

Chemical Reactor Network Modeling of Ammonia Rich-Quench-Lean Combustion Using a Partially Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However, low flammability and a propensity for high nitrogen oxide (NO x ) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NO x emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NO x concentrations below those of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing nonadiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and postflame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors' past work, this arrangement has demonstrated the significant sensitivity of exit NO x to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and nonpremixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NO x emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have been shown to create conditions that are conducive to increased N 2 O formation in the lean stage. In conclusion, the results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia.

Combustion↗