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NASA NTRS2022

A Synopsis of AIRS Global-Mean Clear-Sky Radiance Trends From 2003 to 2020

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global-mean, nadir-view, clear-sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS-5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO2 channels, positive but non-significant trends in the channels over the window regions, and statistically significant positive trends in some of its H2O channels. The best agreements between observed and simulated radiance trends are seen over the CO2 tropospheric channels, while the observed and simulated trends over the CO2 stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H2O channels. The comparison in the H2O channels helps reveal a data continuity issue in the GEOS-5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global-mean trend of AIRS radiances over all its thermal-IR channels.

CO2↗

NASA NTRSDate not supplied

TRIDENT Drill Validation at Mars and Lunar Analog Field Sites

Drilling on Earth is typically a human-intensive activity. Drilling on other planets is further complicated by the lack of prior local field surveys of their target area, hence blindly drilling into uncertain target rocks. Field conditions on the Moon or Mars are also different than for shallow drilling on Earth: lower temperatures and pressures, less power available, low masses (hence less weight-on-bit). Given the cost of transport from Earth, no drilling muds or working fluids are likely to be available to carry away cuttings. And impact-gardened regolith and dust vary mechanically and texturally from most terrestrial soils. The Regolith and Ice Drill for Exploration of New Terrains (TRIDENT) is a rotary-percussive 1m-class drill from Honeybee Robotics. It is low-power (rotary and percussive actuators are 200 W each) and lightweight (<20 kg) with the maximum weight on bit limited to 200 N. TRIDENT has been manifested for the Volatiles Investigating Polar Exploration Rover (VIPER) and PRIME-1 lunar south pole missions in 2024, has previously been field tested at a hot, dry analog site in the Atacama Desert, and in lunar conditions in thermal vacuum chamber tests. TRIDENT was also part of the 2019 Icebreaker Mars Discovery proposal, as well as in the Mars Life Explorer concept. During ARADS tests, drill control and fault recovery automation software enabled hands-off operations of a rover-mounted TRIDENT drill. TRIDENT Drill Analog Site Validation: Past TRIDENT tests in thermal vacuum (TVAC) chambers targeted containers of manufactured lunar simulants with added volatiles. 2022 TRIDENT ambient testing at NASA Ames drilled into cemented lunar simulant materials. Low cuttings-permeability led to cuttings buildup, and drill choking and binding was observed. The Atacama analog site in ARADS had desiccated unconsolidated sediments that did not challenge the TRIDENT design. However, lunar polar regolith is expected to be diverse and heterogeneous with varying clast sizes, with abundant impactites and perhaps subsurface ice deposits. Neither the simulants nor Atacama testing had completely covered the TRIDENT-targeted field characteristics, motivating further analog tests prior to the planned lunar missions. To gain more insight into the behavior of the TRIDENT hardware in diverse impactites and subsurface ice, and to verify the software automation in that environment, in August 2023 TRIDENT was brought to Haughton Crater, a field analog site in the Canadian Arctic. In September 2023 the same drill was brought to the Bishop Tuff in southern California to verify whether drilling binding behaviors previously seen in lunar simulant testing would be observed in naturally occurring fine-grained massive layers. The ~22 Ma Haughton Crater impact structure is located at 75 ̊22’ N, 89 ̊41’ W, on northwestern Devon Island, Nunavut, Canada. Numerous deposits of pale-grey crater-fill polymictic impact-melt breccia are found within the crater with a typical thickness reaching ~125 m or greater and covering ~60 km -2 . An approximately 600m-thick permafrost layer is also present with ice typically found within 0.5-0.6m of the surface. The volcanic tableland north of Bishop, CA exposes densely welded tuff laid down during the eruption that created the Long Valley Caldera at approximately 0.76 Ma. Extensional faults and the Owens River gorge expose cross-sections across the plateau. The area is viewed as an analog site for Mars features believed to be of pyroclastic origin. Results: Haughton Crater.Drilling tests were conducted 8-13 August 2023 at a previously undisturbed area separated 5-10 m from past years’ Drill Hill test sites (75.4208, -089.7613). In six days, TRIDENT drilled 8 holes to nearly 1 m depth each, totaling 7.80 m. The active layer/ice boundary was at ~67 cm depth, with a total of approximately 2.4 m drilled into ice or ice-cemented impact breccia. During drilling, five drill fault states were observed and successfully recovered. Holes 23-1, 4 and 7 were drilled under manual control, using Honeybee’s Thorax user interface. Holes 23-5, 6, and 8 were drilled with the Ames IBexec automated drilling control software. TRIDENT was observed to have little difficulty in the thawed uncemented impact breccia above the active layer boundary, but required percussion to make slower headway in the ice-cemented breccia. In Hole 23-7 (Fig.1), drilling slowed down in a massive unit just above the active-layer boundary (perhaps a large rock extending into the ice-cementation?), with only 7cm progress made in 27 minutes of high auger torque and constant percussion, leading to a choking fault and then a binding fault. A similar pattern had been observed in TRIDENT Rio Tinto test data from 2017 [6] as well as in the 2022laboratory tests.Bishop Tuff.A team from NASA Ames and the US Geological Survey deployed the same TRIDENT drill to Bishop Sites 1B and 1C (37.4203, -118.4289; 37.4265, -118.4215) on 13-16 September 2023, on the Bishop Tuff plateau. A third drill site was used 17-18 September 2023(37.4598, -118.3667) in an abandoned pumice mine. Four holes (totaling 2.5m depth) were drilled into the fine-grained, meters-thick tuff units at Sites 1B and 1C, and a further two boreholes (totaling 1.98m depth) were made at the pumice site. Drill behavior in the tuff below 10 cm depth was similar to that seen at 65-74 cm depth in Haughton Hole 23-7 (Fig. 1) and that seen in the 2022 lab simulant drilling. Drill safety torque limits were exceeded multiple times resulting in drill stops downhole. These freezes then required external added torques (with a pipe wrench) to resume rotation, to unstick the drill for withdrawal. To prevent this choking and binding behavior we found that more-frequent cuttings removal was necessary, e.g., reducing the “drill bite” size from the nominal 10 cm to 2 cm per bite --bringing the auger up to the surface more frequently, as seen in Bishop Site 1C Hole 2 (Fig.2). This permitted slow progress without drill binding and without external interventions. Conversely, TRIDENT drilling in the more porous pumice target material showed no cuttings buildup issue, and single bites as large as 40 cm were demonstrated. Discussion: We observed that TRIDENT easily penetrated unconsolidated heterogeneous soils (both above the active layer boundary at Haughton and previously in the Atacama). Cemented or consolidated targets that were cuttings-permeable (icy impact breccia, pumice) required more energy applied and percussion. However, in non-cuttings-permeable targets (welded microporous tuff, cemented simulants, boulder) TRIDENT was observed to be prone to excessive cuttings accumulation leading to choking/binding faults and stalling. The wedge cutting bit, used by TRIDENT in field tests and in its flight versions, pulverizes the target rock and creates fine cuttings that ideally are transported up the auger spirals for removal. In porous, fractured or vesicular target materials (such as at the Bishop pumice site) a significant portion of the cuttings are pushed aside, but for non-fractured, microporous targets the cuttings remain in the borehole and accumulate. Rock powder is relatively incompressible as a working fluid at only 100-200N downward force (TRIDENT limits) and hence eventual drilling progress slows or stops. Our recommended strategy for improving TRIDENT cuttings removal in massive target units with low cuttings-permeability is to reduce TRIDENT bite sizes when encountering these units, from 10cm to as little as 1-2cm, to effectively bail the accumulating cuttings. This approach was demonstrated to reduce choking and allowed slow progress to continue in cuttings-impermeable microporous target units (viz. the Bishop tuff in our September 2023 tests or cemented simulants in 2022 ambient tests).

robotic drilling↗

DOE OSTI2017

Low-Frequency Shear and Layer-Breathing Modes in Raman Scattering of Two-Dimensional Materials

Ever since the isolation of single-layer graphene in 2004, two-dimensional layered structures have been among the most extensively studied classes of materials. To date, the pool of two-dimensional materials (2DMs) continues to grow at an accelerated pace and already covers an extensive range of fascinating and technologically relevant properties. An array of experimental techniques have been developed and used to fully characterize and understand these properties. In particular, Raman spectroscopy has proven to be a key experimental technique, thanks to its capability to identify minute structural and electronic effects in nondestructive measurements. While high-frequency (HF) intralayer Raman modes have been extensively employed for 2DMs, recent experimental and theoretical progress has demonstrated that low-frequency (LF) interlayer Raman modes are more effective at determining layer numbers and stacking configurations, and provide a unique opportunity to study interlayer coupling. These advantages are due to 2DMs’ unique interlayer vibration patterns where each layer behaves as an almost rigidly moving object with restoring forces corresponding to weak interlayer interactions. Compared to HF Raman modes, the relatively small attention originally devoted to LF Raman modes is largely due to their weaker signal and their proximity to the strong Rayleigh line background, which previously made their detection challenging. Recent progress in Raman spectroscopy with technical and hardware upgrades now makes it possible to probe LF modes with a standard single-stage Raman system and has proven crucial to characterize and understand properties of 2DMs. Here, we present a comprehensive and forward-looking review on the current status of exploiting LF Raman modes of 2DMs from both experimental and theoretical perspectives, revealing the fundamental physics and technological significance of LF Raman modes in advancing the field of 2DMs. We review a broad array of materials, with varying thickness and stacking configurations, discuss the effect of in-plane anisotropy, and present a generalized linear chain model and interlayer bond polarizability model to rationalize the experimental findings. We also discuss the instrumental improvements of Raman spectroscopy to enhance and separate LF Raman signals from the Rayleigh line. Lastly, we highlight the opportunities and challenges ahead in this fast-developing field.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Efficient reactive Brownian dynamics

We develop a Split Reactive Brownian Dynamics (SRBD) algorithm for particle simulations of reaction-diffusion systems based on the Doi or volume reactivity model, in which pairs of particles react with a specified Poisson rate if they are closer than a chosen reactive distance. In our Doi model, we ensure that the microscopic reaction rules for various association and dissociation reactions are consistent with detailed balance (time reversibility) at thermodynamic equilibrium. The SRBD algorithm uses Strang splitting in time to separate reaction and diffusion and solves both the diffusion-only and reaction-only subproblems exactly, even at high packing densities. To efficiently process reactions without uncontrolled approximations, SRBD employs an event-driven algorithm that processes reactions in a time-ordered sequence over the duration of the time step. A grid of cells with size larger than all of the reactive distances is used to schedule and process the reactions, but unlike traditional grid-based methods such as reaction-diffusion master equation algorithms, the results of SRBD are statistically independent of the size of the grid used to accelerate the processing of reactions. We use the SRBD algorithm to compute the effective macroscopic reaction rate for both reaction-limited and diffusion-limited irreversible association in three dimensions and compare to existing theoretical predictions at low and moderate densities. We also study long-time tails in the time correlation functions for reversible association at thermodynamic equilibrium and compare to recent theoretical predictions. Finally, we compare different particle and continuum methods on a model exhibiting a Turing-like instability and pattern formation. Our studies reinforce the common finding that microscopic mechanisms and correlations matter for diffusion-limited systems, making continuum and even mesoscopic modeling of such systems difficult or impossible. We also find that for models in which particles diffuse off lattice, such as the Doi model, reactions lead to a spurious enhancement of the effective diffusion coefficients.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

Western Blot of Stained Proteins from Dried Polyacrylamide Gels

Western blotting of proteins is customarily performed following their separation on polyacrylamide gels, either prior to staining (1) or, as recently reported, following staining (2). We describe here Western blotting with stained gels, which had been dried and some of which had been stored for years. This procedure permits immunological analysis of proteins, to which antisera may have become available only later, or where the application of newly developed sensitive detection methods is desired. Once rehydration of the gels is achieved, proteins can be-transferred to blotting membranes by any appropriate protocol. Proteins stained with Coomassie Blue have to be detected with a non-chromogenic method, such as the film-based enhanced chemiluminescence (ECL)2) procedure (3). Silver stained proteins, which transfer in the colorless form, may be visualized by any detection method, although, because of the usually very low amounts of proteins, detection by ECL is preferable. Blotting of stained proteins from rehydrated gels is as rapid and as quantitative as from freshly prepared gels, in contrast to blotting from wet stained gels, which requires extensive washing and results in low transfer efficiency (2). Together with a photographic record of the gel pattern, unambiguous identification of immunoreactive proteins from complex mixtures is possible. Some further applications of this work are discussed.

Gruber, Claudia↗

DOE OSTI2026

Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP)

Anthropogenic climate change is unfolding rapidly, yet its regional manifestation can be obscured by internal variability. A primary goal of climate science is to identify the externally forced climate response from among the noise of internal variability. Separating the forced response from internal variability can be addressed in climate models by using a large ensemble to average over different possible realizations of internal variability. However, with only one realization of the real world, it is a major challenge to isolate the forced response directly in observations. In the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP), contributors used existing and newly developed statistical and machine learning methods to estimate the forced response over 1950–2022 within individual realizations of the climate system. Participants used neural networks, linear inverse models, fingerprinting methods, and low-frequency component analysis, among other approaches. These methods were trained using large ensembles from multiple climate models and then applied to observations. Here, we evaluate method performance within large ensembles and investigate the estimates of the forced response in observations. Our results show that many different types of methods are skillful for estimating the forced response in climate models, though the relative skill of individual methods varies depending on the variable and evaluation metric. Methods with comparable skill in models can give a wide range of estimates of the forced response pattern in observations, illustrating the epistemic uncertainty in forced response estimates. ForceSMIP gives new insights into the forced response in observations, its uncertainty, and methods for its estimation.

Climate attribution↗

DOE OSTI2017

A novel immunofluorescence method to visualize microtubules in the antiparallel overlaps of microtubule-plus ends in the anaphase and telophase midzone

Cell division, in which duplicated chromosomes are separated into two daughter cells, is the most dynamic event during cell proliferation. Chromosome movement is powered mainly by microtubules, which vary in morphology and are organized into characteristic structures according to mitotic progression. During the later stages of mitosis, antiparallel microtubules form the spindle midzone, and the irregular formation of the midzone often leads to failure of cytokinesis, giving rise to the unequal segregation of chromosomes. However, it is difficult to analyze the morphology of these microtubules because microtubules in the antiparallel overlaps of microtubule-plus ends in the midzone are embedded in highly electron-dense matrices, impeding the access of anti-tubulin antibodies to their epitopes during immunofluorescence staining. Here, we developed a novel method to visualize selectively antiparallel microtubule overlaps in the midzone. When cells are air-dried before fixation, aligned α-tubulin staining is observed and colocalized with PRC1 in the center of the midzone of anaphase and telophase cells, suggesting that antiparallel microtubule overlaps can be visualized by this method. In air-dried cells, mCherry-α-tubulin fluorescence and β-tubulin staining show almost the same pattern as α-tubulin staining in the midzone, suggesting that the selective visualization of antiparallel microtubule overlaps in air-dried cells is not attributed to an alteration of the antigenicity of α-tubulin. Taxol treatment extends the microtubule filaments of the midzone in air-dried cells, and nocodazole treatment conversely decreases the number of microtubules, suggesting that unstable microtubules are depolymerized during the air-drying method. It is of note that the air-drying method enables the detection of the disruption of the midzone and premature midzone formation upon Aurora B and Plk1 inhibition, respectively. These results suggest that the air-drying method is suitable for visualizing microtubules in the antiparallel overlaps of microtubule-plus ends of the midzone and for detecting their effects on midzone formation. - Highlights: • A novel method to visualize antiparallel microtubule overlaps is developed. • Unstable microtubules are depolymerized during an air-drying method. • This method can detect the effect of compounds on antiparallel microtubule overlaps.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Improving ICARUS Track Reconstruction Algorithms

The ICARUS experiment is part of the Short-Baseline Neutrino (SBN) program at Fermilab. The main goal of the experiment is to investigate the possibility of sterile neutrinos in the O(1 eV) mass region and provide clarification of the anomaly detected from the Liquid Scintillator Neutrino Detector (LSND) and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber (LAr-TPC), that can provide excellent 3D imaging and calorimetric reconstruction of any ionizing particles. This detection technique allows a detailed study of neutrino interactions, spanning a wide energy spectrum (from a few keV to several hundreds of GeV). The detector consists of two identical adjacent modules, filled with a total of 760 tons of ultra-pure liquid argon. Each module houses two LAr-TPCs separated by a common cathode with a maximum drift distance of 1.5 m, equivalent to about 1 ms drift time for the nominal $500$ V/m electric drift field. The anode is made of three parallel wire planes positioned 3 mm apart, where the stainless-steel wires are oriented on each plane at a different angle with respect to the horizontal direction ($+60^\degree$,$-60^\degree$,$0^\degree$). The first two planes (Induction 1 and Induction 2) provide a non-destructive charge measurement, whereas the ionization charge is fully collected by the last collection plane. In total, 53248 wires with a 3 mm pitch and length up to 9 m are installed in the detector. In the first stage of the reconstruction, segments of waveforms corresponding to physical signals (hits) are searched for in the deconvolved wire waveform with a threshold-based hit-finding algorithm. Each hit is then fitted with a Gaussian, whose area is proportional to the number of drift electrons generating the signal. In the second stage of the reconstruction, hits are passed as input to Pandora, a framework software composed of different pattern recognition algorithms, that performs a 3D reconstruction of the full image recorded in the collected event, including the identification of interaction vertices and tracks and showers inside the TPC. These are organized into a hierarchical structure (called slice) of particles generated starting from a primary interaction vertex. In some cases, related to the inefficiencies in the hit detection or excessive deflection of the particle trajectory, Pandora breaks the particle's track into two or more smaller pieces and considers each piece as an independent track. We studied this phenomenon focusing on primary muons from ν_μ CC interactions contained in a single module with a track at least 20 cm long, to exclude delta rays. The study determined that about $7-8\%$ of the muon tracks are broken. Approximately $80\%$ of the times, Pandora assigns all segments of the track to the same slice (intra-slice track split), while in the remaining $20\%$ of the cases, one of the segments is associated with another slice (extra-slice track split). To mitigate this phenomenon, we designed an algorithm that detects and stitches the tracks broken by Pandora for the intra-slice split. In Monte Carlo simulations, the algorithm showed an efficiency exceeding $80\%$ and a purity exceeding $93\%$.

Ricci, Alessandro Maria [Pisa U.; INFN, Pisa] (ORC↗

DOE OSTI2023

Backup Power Performance of Solar-plus-Storage Systems during Routine Power Interruptions: A Case Study Application of Berkeley Lab’s PRESTO Model

This technical brief estimates the expected performance of a solar photovoltaic and energy storage system (PVESS) for providing backup power during short-duration power interruption events, accounting for the unpredictable nature of those events. The analysis relies on the Power Reliability Event Simulation TOol (PRESTO), a publicly available model developed by Berkeley Lab to simulate the occurrence of short-duration power interruption events at the county-level. A separate storage dispatch model is then used to simulate PVESS operation and backup performance for each of the large number of interruption events produced by PRESTO. In performing this simulation, the analysis accounts for how the customer operates its battery on a day-to-day basis—in this case, we assume the battery is cycled each day in response to time-of-use rates—and how that, in turn, impacts the battery’s state of charge at the beginning of each interruption event. The analysis presented here is intended to demonstrate an application of the PRESTO model as well as to illustrate some of the key determinants of PVESS backup power performance during short-duration power interruption events. The analysis focuses initially on a typical single-family home in Maricopa County, Arizona, and includes a limited set of scenarios related to system sizing, backup power configuration, and whether the customer charges its battery storage system from the grid during normal operating conditions. The analysis also presents comparative results for two other counties, in Massachusetts (Middlesex) and California (Los Angeles), illustrating how regional differences in climate, interruption patterns, and retail rate structures can affect PVESS performance as a backup power source. In the conclusions, we highlight a number of other important considerations for evaluating PVESS backup power capabilities.

14 SOLAR ENERGY↗

DOE OSTI2019

The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa

The impact of climate variability on groundwater storage has received limited attention despite widespread dependence on groundwater as a resource for drinking water, agriculture and industry. Here, we assess the climate anomalies that occurred over Southern Africa (SA) and East Africa, south of the Equator (EASE), during the major El Niño event of 2015–2016, and their associated impacts on groundwater storage, across scales, through analysis of in situ groundwater piezometry and Gravity Recovery and Climate Experiment (GRACE) satellite data. At the continental scale, the El Niño of 2015–2016 was associated with a pronounced dipole of opposing rainfall anomalies over EASE and Southern Africa, north–south of ~12°S, a characteristic pattern of the El Niño–Southern Oscillation (ENSO). Over Southern Africa the most intense drought event in the historical record occurred, based on an analysis of the cross-scale areal intensity of surface water balance anomalies (as represented by the standardised precipitation evapotranspiration index – SPEI), with an estimated return period of at least 200 years and a best estimate of 260 years. Climate risks are changing, and we estimate that anthropogenic warming only (ignoring changes to other climate variables, e.g. precipitation) has approximately doubled the risk of such an extreme SPEI drought event. These surface water balance deficits suppressed groundwater recharge, leading to a substantial groundwater storage decline indicated by both GRACE satellite and piezometric data in the Limpopo basin. Conversely, over EASE during the 2015–2016 El Niño event, anomalously wet conditions were observed with an estimated return period of ~10 years, likely moderated by the absence of a strongly positive Indian Ocean zonal mode phase. The strong but not extreme rainy season increased groundwater storage, as shown by satellite GRACE data and rising groundwater levels observed at a site in central Tanzania. We note substantial uncertainties in separating groundwater from total water storage in GRACE data and show that consistency between GRACE and piezometric estimates of groundwater storage is apparent when spatial averaging scales are comparable. These results have implications for sustainable and climate-resilient groundwater resource management, including the potential for adaptive strategies, such as managed aquifer recharge during episodic recharge events.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗

NASA NTRS1995

Simultaneous prenoon and postnoon observations of three field-aligned current systems from Viking and DMSP-F7

The spatial structure of dayside large-scale field-aligned current (FAC) systems is examined by using Viking and Defense Meteorological Satellite Program-F7 (DMSP-F7) data. We focus on four events in which the satellites simultaneously observed postnoon and prenoon three FAC systems: the region 2, the region 1, and the mantle (referred to as midday region O) systems, from equatorward to poleward. These events provide the most solid evidence to date that the midday region O system is a separate and unique FAC system, and is not an extension of the region 1 system from other local times. The events are examined comprehensively by making use of a mulit-instrumental data set, which includes magnetic field, particle flux, electric field, auroral UV image data from the satellites, and the Sondrestrom convection data. The results are summarized as follows: (1) Region 2 currents flow mostly in the central plasma sheet (CPS) precipitation region, often overlapping with the boundary plasma sheet (BPD) at their poleward edge. (2) The region 1 system is located in the core part of the auroral oval and is confined in a relatively narrow range in latitude which includes the convection reversal. The low-latitude boundary layer, possibly including the outer part of the plasma sheet, and the external cusp are the major source regions of dayside region 1 currents. (2) Midday region O currents flow on open field lines and are collocated with the shear of antisunward convection flows with velocites decreasing poleward. On the basis of these results we support the view that both prenoon and postnoon current systems consist of the three-sheet structure when the disctortion ofthe convection pattern associated with interplanetary magnetic field (IMF) B(sub Y) is small and both morningside and eveningside convection cells are crescent-shaped. We also propose that the midday region O and a part of the region 1 systems are closely coupled to the same source.

Ohtani, S.↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Application of Cyber-Informed Engineering for Protecting BESS

This white paper synthesizes an array of crucial grid services provided by BESS technology, assesses its architecture and communications, and presents a case study for analysis against the principles introduced by Cyber-Informed Engineering (CIE). Furthermore, in walking through the analysis, this paper presents a framework to evaluate risks and solutions when considering BESS components. Asset owners and buyers could perform this analysis to assess their BESS product implementations, alternative inverter-based resources (IBR), and energy management systems (EMS). Battery systems fulfill various roles contingent on the unique market demands and the specific challenges presented by regional grid infrastructures. These roles also vary due to the differing utility models for ownership and operation, which are adapted to meet regional and local capabilities and requirements. Concerns have been raised regarding the potential for adversaries to exploit knowledge of battery operational patterns to orchestrate decisive attacks. However, the security of operational data for these systems may not be the primary vulnerability, as much of this information is already well-understood within the community. Applying a modest degree of subject matter expertise can often yield valuable predictions regarding how a battery will respond under certain conditions, such as grid emergencies, high or low-temperature days, Public Safety Power Shutoff (PSPS) events, and outages. The operational characteristics of batteries are well-documented, and their capabilities, including the risks associated with misoperation and the resulting consequences, are published and understood within the industry. CIE practices represent the next step in gaining functional assurance and providing an acceptable level of risk, regardless of whether a battery vendor can support a trusted and validated supply chain. While this issue has exacerbated supply chain challenges, it is not an isolated condition. This foreign supply route is the primary source of BESS for the U.S. market. Significant efforts are underway through the Bipartisan Infrastructure Law (BIL) to change that. Still, strategic short-term operational mitigations are needed to ensure the security of our operational technology (OT) systems, which are enhanced by instilling trust and are separate from vendors implementing CIE principles.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Packed Bed Reactor Experiment (PBRE)-2: Pressure Drop Measurements in Microgravity

Single and two-phase flow through porous media are encountered on ground and in space in numerous applications related to life support systems, fuel cells, chemical/materials processing and transporting nutrients to plants. These systems operate differently in the microgravity environment encountered in space travel because the density differences no longer cause the phases to separate or “drain” under the body force of gravity. In the absence of gravity, the interfacial or capillary forces play a more significant role in determining the operational variables such as phase distribution, liquid holdup, and pressure drop especially when the liquid inertia and viscous forces are at minimum. Lower liquid flow rates in air-water two-phase flows represent the case for most of the space processes that depend on two-phase flows in porous media. The Packed Bed Reactor Experiment (PBRE) was developed and flown on the International Space Station (ISS) by NASA to extend a series of fundamental studies of gas-liquid flows through porous media. The goal of the this series of flight experiments (PBRE-1 and PBRE-2) is to better understand the hydrodynamics of two phase flows in porous media in flow regimes dominated by inertia and viscous effects and understanding the role of the interfacial forces and their role in determining the flow dynamics. The flight experiments were preceded by a series of low gravity experiments performed on the low gravity aircraft. These experiments led to the development of a semi-empirical two-phase pressure drop and flow pattern transition in support of a number of reactor beds planned for water reclamation processes onboard of the international space station. The PBRE flight experiment was designed to deliver a wide range of tightly controlled gas (nitrogen) and liquid (water) flows to one of two interchangeable test sections differing only in the type of internal packing material. In this paper, we describe the PBRE-2 experiment and present preliminary low gravity data on pressure drop and compare with semi-empirical model pressure drop predictions. This work is supported by the National Aeronautics and Space Administration (NASA) under grant no. 80NSSC20K0830

Suratman Number↗

NASA NTRSDate not supplied

Pressure Gradient and Gas Hold-Up in Two-Phase Flows through Porous Media in Microgravity

Single and two-phase flow through porous media are encountered on ground and in space in numerous applications related to life support systems, fuel cells, chemical/materials processing and transporting nutrients to plants. These systems operate differently in the microgravity environment encountered in space travel because the density differences no longer cause the phases to separate or “drain” under the body force of gravity. In the absence of gravity, the interfacial or capillary forces play a more significant role in determining the operational variables such as phase distribution, liquid holdup, and pressure drop especially when the liquid inertia and viscous forces are at minimum. Lower liquid flow rates in air-water two-phase flows represent the case for most of the space processes that depend on two-phase flows in porous media. The Packed Bed Reactor Experiment (PBRE) was developed and flown on the International Space Station (ISS) by NASA to extend a series of fundamental studies of gas-liquid flows through porous media. The goal of the this series of flight experiments (PBRE-1 and PBRE-2) is to better understand the hydrodynamics of two phase flows in porous media in flow regimes dominated by inertia and viscous effects and understanding the role of the interfacial forces and their role in determining the flow dynamics. The flight experiments were preceded by a series of low gravity experiments performed on the low gravity aircraft. These experiments led to the development of a semi-empirical two-phase pressure drop and flow pattern transition in support of a number of reactor beds planned for water reclamation processes onboard of the international space station. The PBRE flight experiment was designed to deliver a wide range of tightly controlled gas (nitrogen) and liquid (water) flows to one of two interchangeable test sections differing only in the type of internal packing material. In this presentation, we describe the PBRE-2 experiment and present preliminary low gravity data on pressure drop and gas hold-up and compare with semi-empirical model pressure drop predictions.

Brian Motil↗

DOE OSTI2020

Computationally Aided Design of a Small-Scale Waste-Glass Melter - 20452

To provide mission support to the WTP for the vitrification of legacy nuclear tank waste at the Hanford site, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The waste stored in underground tanks will be separated into HLW and LAW fractions, where the majority is LAW by mass (approximately 90%) and HLW by activity (greater than 95%). The first tank waste to be processed at the WTP will be LAW. Because Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high cost of full-scale radioactive operations and to provide an engineering platform in close proximity to local operations staff. The objectives of this computational modeling effort are to produce process conditions like those encountered in the WTP LAW melters and to minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area or melter-glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models was developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten-glass pool and within the bulk-glass pool. Since melt rate correlates with the velocity underneath the cold cap, this information can be used to select design features that produce the highest gains. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗