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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Simulations of ocean deoxygenation in the historical era: insights from forced and coupled models

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O 2 ). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O 2 inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O 2 trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O 2 inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×10 14 [mol/decade] for OMIP1, -0.37 ± 0.15×10 14 [mol/decade] for OMIP2, and -1.06 ± 0.68×10 14 [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O2 inventory for the latest observations based on the World Ocean Database 2018 is -0.98×10 14 [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O 2 inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O 2 . Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible future coordinated ocean biogeochemistry simulations to fill in gaps and unravel the mechanisms controlling the O 2 changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
DOE OSTI2021

Black hole induced false vacuum decay from first principles

We provide a method to calculate the rate of false vacuum decay induced by a black hole. The method uses complex tunneling solutions and consistently takes into account the structure of different quantum vacua in the black hole metric via boundary conditions. The latter are connected to the asymptotic behavior of the time-ordered Green’s function in the corresponding vacua. We illustrate the technique on a two-dimensional toy model of a scalar field with inverted Liouville potential in an external background of a dilaton black hole. We analytically derive the exponential suppression of tunneling from the Boulware, Hartle-Hawking and Unruh vacua and show that they are parametrically different. The Unruh vacuum decay rate is exponentially smaller than the decay rate of the Hartle-Hawking state, though both rates become unsuppressed at high enough black hole temperature. We interpret the vanishing suppression of the Unruh vacuum decay at high temperature as an artifact of the two-dimensional model and discuss why this result can be modified in the realistic case of black holes in four dimensions.

2D Gravity↗
NASA NTRS2001

Measurement of Separated Flow Structures Using a Multiple-Camera DPIV System

A novel multiple-camera system for the recording of digital particle image velocimetry (DPIV) images acquired in a two-dimensional separating/reattaching flow is described. The measurements were performed in the NASA Langley Subsonic Basic Research Tunnel as part of an overall series of experiments involving the simultaneous acquisition of dynamic surface pressures and off-body velocities. The DPIV system utilized two frequency-doubled Nd:YAG lasers to generate two coplanar, orthogonally polarized light sheets directed upstream along the horizontal centerline of the test model. A recording system containing two pairs of matched high resolution, 8-bit cameras was used to separate and capture images of illuminated tracer particles embedded in the flow field. Background image subtraction was used to reduce undesirable flare light emanating from the surface of the model, and custom pixel alignment algorithms were employed to provide accurate registration among the various cameras. Spatial cross correlation analysis with median filter validation was used to determine the instantaneous velocity structure in the separating/reattaching flow region illuminated by the laser light sheets. In operation the DPIV system exhibited a good ability to resolve large-scale separated flow structures with acceptable accuracy over the extended field of view of the cameras. The recording system design provided enhanced performance versus traditional DPIV systems by allowing a variety of standard and non-standard cameras to be easily incorporated into the system.

Humphreys, William M., Jr.↗
DOE OSTI2023

Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows

The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.

high pressure reverse osmosis↗
NASA NTRS2017

Meteoroid Environment Modeling: The Meteoroid Engineering Model and Shower Forecasting

The meteoroid environment is often divided conceptually into meteor showers and the sporadic meteor background. It is commonly but incorrectly assumed that meteoroid impacts primarily occur during meteor showers; instead, the vast majority of hazardous meteoroids belong to the sporadic complex. Unlike meteor showers, which persist for a few hours to a few weeks, sporadic meteoroids impact the Earth's atmosphere and spacecraft throughout the year. The Meteoroid Environment Office (MEO) has produced two environment models to handle these cases: the Meteoroid Engineering Model (MEM) and an annual meteor shower forecast. The sporadic complex, despite its year-round activity, is not isotropic in its directionality. Instead, their apparent points of origin, or radiants, are organized into groups called "sources". The speed, directionality, and size distribution of these sporadic sources are modeled by the Meteoroid Engineering Model (MEM), which is currently in its second major release version (MEMR2) [Moorhead et al., 2015]. MEM provides the meteoroid flux relative to a user-provided spacecraft trajectory; it provides the total flux as well as the flux per angular bin, speed interval, and on specific surfaces (ram, wake, etc.). Because the sporadic complex dominates the meteoroid flux, MEM is the most appropriate model to use in spacecraft design. Although showers make up a small fraction of the meteoroid environment, they can produce significant short-term enhancements of the meteoroid flux. Thus, it can be valuable to consider showers when assessing risks associated with vehicle operations that are brief in duration. To assist with such assessments, the MEO issues an annual forecast that reports meteor shower fluxes as a function of time and compares showers with the time-averaged total meteoroid flux. This permits missions to do quick assessments of the increase in risk posed by meteor showers. Section II describes MEM in more detail and describes our current efforts to improve its characteristics for a future release. Section III describes the annual shower forecast and highlights recent improvements made to its algorithm and inputs.

Moorhead, Althea V.↗
NASA NTRS1999

The Chancellor's Model School Project (CMSP)

What does it take to create and implement a 7th to 8th grade middle school program where the great majority of students achieve at high academic levels regardless of their previous elementary school backgrounds? This was the major question that guided the research and development of a 7-year long project effort entitled the Chancellor's Model School Project (CMSP) from September 1991 to August 1998. The CMSP effort conducted largely in two New York City public schools was aimed at creating and testing a prototype 7th and 8th grade model program that was organized and test-implemented in two distinct project phases: Phase I of the CMSP effort was conducted from 1991 to 1995 as a 7th to 8th grade extension of an existing K-6 elementary school, and Phase II was conducted from 1995 to 1998 as a 7th to 8th grade middle school program that became an integral part of a newly established 7-12th grade high school. In Phase I, the CMSP demonstrated that with a highly structured curriculum coupled with strong academic support and increased learning time, students participating in the CMSP were able to develop a strong foundation for rigorous high school coursework within the space of 2 years (at the 7th and 8th grades). Mathematics and Reading test score data during Phase I of the project, clearly indicated that significant academic gains were obtained by almost all students -- at both the high and low ends of the spectrum -- regardless of their previous academic performance in the K-6 elementary school experience. The CMSP effort expanded in Phase II to include a fully operating 7-12 high school model. Achievement gains at the 7th and 8th grade levels in Phase II were tempered by the fact that incoming 7th grade students' academic background at the CMSP High School was significantly lower than students participating in Phase 1. Student performance in Phase II was also affected by the broadening of the CMSP effort from a 7-8th grade program to a fully functioning 7-12 high school which as a consequence lessened the focus and structure available to the 7-8th grade students and teachers -- as compared to Phase I. Nevertheless, the CMSP does represent a unique curriculum model for 7th and 8th grade students in urban middle schools. Experience in both Phase I and Phase II of the project allowed the CMSP to be developed and tested along the broad range of parameters and characteristics that embody an operating public school in an urban environment.

Lopez, Gil↗
DOE OSTI2024

Variation in forest root image annotation by experts, novices, and AI

Abstract Background The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. Results Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation ( p = 0.01). The CNN net root length change results were closer to manual ( p = 0.08) but there remained substantial variation. Conclusions Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Handy, Grace↗
DOE OSTI2024

Design and evaluation of a low-cost sensor node for near-background methane measurement

Abstract. We developed a low-cost methane sensing node incorporating two metal oxide (MOx) sensors (Figaro Engineering TGS2611-E00 and TGS2600), humidity and temperature sensing, data storage, and telemetry. We deployed the prototype sensor alongside a reference methane analyzer at two sites: one outdoors and one indoors. We collected data at each site for several months across a range of environmental conditions (particularly temperature and humidity) and methane levels. We explored calibration models to investigate the performance of our system and its suitability for methane background monitoring and enhancement detection, first selecting a linear regression to fit a sensor baseline response and then fitting methane response by the sensor deviation from baseline. We achieved moderate accuracy in a 2 to 10 ppm methane range compared to data from the reference analyzer (RMSE < 0.6 ppm), but we found that the sensor response varied over time, possibly as a result of changes in non-targeted gas concentrations. We suggest that this cross sensitivity may be responsible for mixed results in previous studies. We discuss the implications of our results for the use of these and similar inexpensive MOx sensors for methane monitoring in the 2 to 10 ppm range.

Furuta, Daniel↗
DOE OSTI2021

A consistent and conservative model and its scheme for N -phase- M -component incompressible flows

Here, we propose a consistent and conservative model for multiphase and multicomponent incompressible flows, where there can be arbitrary numbers of phases and components. Each phase has a background fluid called the pure phase, each pair of phases is immiscible, and components are dissolvable in some specific phases. The model is developed based on the multiphase Phase-Field model including the contact angle boundary condition, the diffuse domain approach, and the analyses on the proposed consistency conditions for multiphase and multicomponent flows. The model conserves the mass of individual pure phases, the amount of each component in its dissolvable region, and thus the mass of the fluid mixture, and the momentum of the flow. It ensures that no fictitious phases or components can be generated and that the summation of the volume fractions from the Phase-Field model is unity everywhere so that there is no local void or overfilling. It satisfies a physical energy law and it is Galilean invariant. A corresponding numerical scheme is developed for the proposed model, whose formal accuracy is 2nd-order in both time and space. It is shown to be consistent and conservative and its solution is demonstrated to preserve the Galilean invariance and energy law. Numerical tests indicate that the proposed model and scheme are effective and robust to study various challenging multiphase and multicomponent flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

No H 0 assistance from assisted quintessence

Early dark energy, as a proposed solution to the Hubble tension, faces an additional “why now” problem. Why should dark energy emerge just prior to recombination, billions of years before the onset of cosmic acceleration? Assisted quintessence explains this connection by positing that multiple scaling fields build up over time to drive the present-day cosmic acceleration. In this framework, early dark energy is inevitable. Yet, we show that scaling also leads to the demise of the scenario: the same feature that solves the coincidence problem then spoils a concordance of the Hubble constant inferred from the cosmic microwave background with that from the local distance ladder. In conclusion, the failure of the model offers a novel lesson on the ability of new physics to resolve the Hubble tension.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Testing the pressure-confined Ly alpha cloud model

The Ly-alpha absorption line forest, seen in quasar spectra, is generally interpreted as being due to cosmologically distributed 'clouds' of primordial gas. Analyses of the observations reveal that the number distribution can be described by power laws: dN/dz is proportional to (1 + z)(sup gamma) and dN/dN(sub HI) is proportional to N(sub HI)(sup -beyda), where N(sub HI) is the HI column density. The typical values for power law indices range between 2 is approximately less than gamma is approximately less than 2.6 and 1.7 is approximately less than gamma is approximately less than 1.9. One model postulates that the Ly-alpha clouds are optically thin entities, photoionized by the background UV flux, J(sub nu) is proportional to (1 + z)(sup j), and confined by an adiabatically evolving intercloud medium (ICM): P(z) is proportional to (1 + z)(sup 5). Analytic studies of this model suggest that the ensuing Ly-alpha line statistics can account for the observations (in particular, the dN/dz and the dN/dN(sub HI) distributions) if the cloud mass spectrum is a power law dN/dN is proportional to M(sup -delta), delta is approximately 1.9, and j is approximately 4. One of the simplifying assumptions incorporated into these studies is the existence of a large mass range for the clouds at all epochs, the validity of which is questionable. The pressure-confined model is investigated using a 1-D spherically symmetric hydrodynamical code to simulate cloud evolution over the epoch 1.8 less than z less than 6. This enables us to relax many of the assumptions incorporated in the analytic studies.

Babul, Arif↗
NASA NTRS1973

Detection of turbidity dynamics in Tampa Bay, Florida using multispectral imagery from ERTS-1

In 1970, Congress authorized the deepening of the Tampa Bay channel (Rivers and Harbors Act of 1970) from 34 to 44 feet. In order to determine the effects of this deepening on circulation, water quality, and biota, during and after the construction, the U.S. Geological Survey, in cooperation with the Tampa Port Authority, has collected data and developed a digital simulation model of the bay. In addition to data collected using conventional tools, use is being made of data collected from ERTS-1. Return beam vidicon (RBV) multispectral data were collected, while a shell dredging barge was operating in the bay, and used for turbidity recognition and unique spectral signatures representative of type and amount of material in suspension. A three-dimensional concept of the dynamics of the plume was achieved by superimposing the parts of the plume recognized in each RBV band. This provides a background for automatic computer processing of ERTS data and three-dimensional modeling of turbidity plumes.

Coker, A. E.↗
DOE OSTI2020

hi_class background evolution, initial conditions and approximation schemes

Cosmological datasets have great potential to elucidate the nature of dark energy and test gravity on the largest scales available to observation. Theoretical predictions can be computed with hi_class (www.hiclass-code.net), an accurate, fast and flexible code for linear cosmology, incorporating a wide range of dark energy theories and modifications to general relativity. We introduce three new functionalities into hi_class: (1) Support for models based on covariant Lagrangians, including a constraint-preserving integration scheme for the background evolution and a series of worked-out examples: Galileon, nKGB, quintessence (monomial, tracker) and Brans-Dicke. (2) Consistent initial conditions for the scalar-field perturbations in the deep radiation era, identifying the conditions under which modified-gravity isocurvature perturbations may grow faster than adiabatic modes leading to a loss of predictivity. (3) An automated quasistatic approximation scheme allowing order-of-magnitude improvement in computing performance without sacrificing accuracy for wide classes of models. These enhancements bring the treatment of dark energy and modified gravity models to the level of detail comparable to software tools restricted to standard $\Lambda$CDM cosmologies. Finally, the hi_class code is publicly available (https://github.com/miguelzuma/hi_class_public), ready to explore current data and prepare for next-generation experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗
DOE OSTI2024

Factorized visual representations in the primate visual system and deep neural networks

Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (‘invariance’), represented in non-interfering subspaces of population activity (‘factorization’) or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters – lighting, background, camera viewpoint, and object pose – in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.

59 BASIC BIOLOGICAL SCIENCES↗