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At least 1,279 records · Page 71

In-situ Raman Instrumentation and Measurements in Supercritical Water Oxidation Systems

Due to the advent of recent advances in reactor designs and operational procedures, renewed attention has been given to a host of supercritical water oxidation (SCWO) technology applications. This includes resource recovery, water reclamation, and solid waste destruction. SCWO is often recognized as a “green technology” because of its ability to extract useful energy while producing benign products from environmentally challenging waste streams (e.g., wet organic wastes, pharmaceutical wastes, military wastes). The present work was motivated by NASA’s interests in solid waste management and water recovery for long-duration space missions. To that end, the main focus of this paper is to present work on characterizing the behavior of supercritical water oxidation systems utilizing state of the art laser Raman spectroscopy. The main benefit of Raman diagnostics is its ability to identify chemical composition and to measure concentrations of the compounds involved in the reaction. Two separate Raman systems for SCWO measurements that have been developed for this study will be described. The first system is a 2-D traversing system useful for making in-situ measurements in conditions where spatial gradients of species and temperature are important and has been successfully utilized in making species (ethanol, oxygen, water, nitrogen and carbon dioxide) concentrations and temperature measurements in ethanol hydrothermal jet flames. The second system is a packaged modular Raman probe unit for portable deployment to different reactors and is more suitable for relatively homogeneous systems such as a batch reactor. The design, development, and examples of obtained results from both systems will be presented for various reactant streams. Reaction rate and fuel conversion estimates from chemistry models will also be presented.

supercritical water oxidation↗

Dynamic Motions of Topological Defects in Nematic Liquid Crystals under Spatial Confinement

Abstract Topological defects (TDs) have become a sensational topic due to their significant influence on the unusual optical and physiochemical characteristics of the material. To facilitate their application across a wide range of disciplines it is desirable to analyze and gain fundamental understanding of TDs in both equilibrium and nonequilibrium systems. Liquid crystals (LCs) are considered an ideal system for study given the direct visualization of TDs and a straightforward analyzation process. In addition to the equilibrium morphology of LC TDs, it is also of great interest to track and control the formation and annihilation of defects during thermodynamic processes. However, controlling the dynamic behavior of formed defects remains a challenge. Here, nematic LCs confined in a cell exhibiting surfaces with periodic anchoring conditions containing surface topography are relied on. The effects of patterned surface characteristics such as width, periodicity, and degree of curvature on defects dynamic motion, stabilization, and annihilation are explored. The computational experiments recapitulate the TDs transition path and provide free energy‐based predictions of critical distances for defect annihilation. Taken together, this simple approach offers a promising opportunity to control the dynamics of TDs in LCs through chemical patterned surfaces with topography.

36 MATERIALS SCIENCE↗

Pre-Stall Behavior of a Transonic Axial Compressor Stage via Time-Accurate Numerical Simulation

CFD calculations using high-performance parallel computing were conducted to simulate the pre-stall flow of a transonic compressor stage, NASA compressor Stage 35. The simulations were run with a full-annulus grid that models the 3D, viscous, unsteady blade row interaction without the need for an artificial inlet distortion to induce stall. The simulation demonstrates the development of the rotating stall from the growth of instabilities. Pressure-rise performance and pressure traces are compared with published experimental data before the study of flow evolution prior to the rotating stall. Spatial FFT analysis of the flow indicates a rotating long-length disturbance of one rotor circumference, which is followed by a spike-type breakdown. The analysis also links the long-length wave disturbance with the initiation of the spike inception. The spike instabilities occur when the trajectory of the tip clearance flow becomes perpendicular to the axial direction. When approaching stall, the passage shock changes from a single oblique shock to a dual-shock, which distorts the perpendicular trajectory of the tip clearance vortex but shows no evidence of flow separation that may contribute to stall.

Chen, Jen-Ping↗

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

AICCA: AI-Driven Cloud Classification Atlas

Clouds play an important role in the Earth’s energy budget, and their behavior is one of the largest uncertainties in future climate projections. Satellite observations should help in understanding cloud responses, but decades and petabytes of multispectral cloud imagery have to date received only limited use. This study describes a new analysis approach that reduces the dimensionality of satellite cloud observations by grouping them via a novel automated, unsupervised cloud classification technique based on a convolutional autoencoder, an artificial intelligence (AI) method good at identifying patterns in spatial data. Our technique combines a rotation-invariant autoencoder and hierarchical agglomerative clustering to generate cloud clusters that capture meaningful distinctions among cloud textures, using only raw multispectral imagery as input. Cloud classes are therefore defined based on spectral properties and spatial textures without reliance on location, time/season, derived physical properties, or pre-designated class definitions. We use this approach to generate a unique new cloud dataset, the AI-driven cloud classification atlas (AICCA), which clusters 22 years of ocean images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua and Terra instruments—198 million patches, each roughly 100 km × 100 km (128 × 128 pixels)—into 42 AI-generated cloud classes, a number determined via a newly-developed stability protocol that we use to maximize richness of information while ensuring stable groupings of patches. AICCA thereby translates 801 TB of satellite images into 54.2 GB of class labels and cloud top and optical properties, a reduction by a factor of 15,000. The 42 AICCA classes produce meaningful spatio-temporal and physical distinctions and capture a greater variety of cloud types than do the nine International Satellite Cloud Climatology Project (ISCCP) categories—for example, multiple textures in the stratocumulus decks along the West coasts of North and South America. We conclude that our methodology has explanatory power, capturing regionally unique cloud classes and providing rich but tractable information for global analysis. AICCA delivers the information from multi-spectral images in a compact form, enables data-driven diagnosis of patterns of cloud organization, provides insight into cloud evolution on timescales of hours to decades, and helps democratize climate research by facilitating access to core data.

97 MATHEMATICS AND COMPUTING↗

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Laymon, Charles A.↗

The Dynamics of Coupled Oscillator Phase Control

Arrays of coupled oscillators have been proposed as means of realizing high power rf sources via coherent spatial power combining. In such applications, a uniform phase distribution over the aperture is usually desired. However, it has been shown that by detuning some of the oscillators away from the oscillation frequency of the ensemble of oscillators, one may achieve other useful aperture phase distributions. Of particular interest among those achievable are linear phase distributions because these result in steering of the output rf beam away from the broadside direction. The theory describing the behavior of such arrays of coupled oscillators is quite complicated since the phenomena involved are inherently nonlinear. However, a simplified theory has been developed which facilitates intuitive understanding. This simplified theory is based on a "continuum model" in which the aperture phase is represented by a continuous function of the aperture coordinates. A challenging aspect of the development of this theory is the derivation of appropriate boundary conditions at the edges or ends of the array.

Pogorzelski, R. J.↗

Laser-induced digital oxidation for copper-based flexible photodetectors

Copper oxide compounds (Cu x O) with bandgaps of 1.3–2.1 eV (CuO) and 2.1–2.6 eV (Cu 2 O) have been investigated as promising p-type semiconducting materials. Cu x O is generally obtained by deposition or thermal oxidation, but those methods are not optimal for flexible substrates. Furthermore, additional patterning steps are required to fabricate devices. In this work, we present an easy, controllable method to fabricate a metal-semiconductor-metal (MSM) photodetector using laser-induced oxidation of a thin Cu film. After laser irradiation, the Cu film is heated under ambient conditions, and this leads to a thermal oxidation reaction, in which Cu oxide is monolithically formed in the Cu film and a Cu-Cu x O-Cu MSM structure is produced. Since the laser offers localized heating, an arbitrary CuxO pattern can be written in the Cu film by spatially controlled heating. In addition, by optimizing the heating time, the laser-induced oxidation can be successfully performed even on a flexible substrate. To study the laser-induced oxidation, we examined the correlation between laser parameters and the oxidation pattern and analyzed the composition using scanning electron microscopy, Raman spectroscopy, and X-ray photoemission spectroscopy. Furthermore, we measured the transient photoresponse and employed scanning photocurrent microscopy to investigate the mechanism of carrier transport behavior.

36 MATERIALS SCIENCE↗

A comparative study of machine learning models for predicting the state of reactive mixing

Mixing phenomena are important mechanisms controlling flow, species transport, and reaction processes in fluids and porous media. Accurate predictions of reactive mixing are critical for many Earth and environmental science problems such as contaminant fate and remediation, macroalgae growth, and plankton biomass evolution. Here, to investigate the evolution of mixing dynamics under different scenarios (e.g., anisotropy, fluctuating velocity fields), a finite-element-based numerical model was built to solve the fast, irreversible bimolecular reaction-diffusion equations to simulate a range of reactive-mixing scenarios. A total of 2,315 simulations were performed using different sets of model input parameters comprising various spatial scales of vortex structures in the velocity field, time-scales associated with velocity oscillations, the perturbation parameter for the vortex-based velocity, anisotropic dispersion contrast (i.e., ratio of longitudinal-to-transverse dispersion), and molecular diffusion. The outputs comprised concentration profiles of reactants and products. The inputs to and outputs from these simulations were concatenated into feature and label matrices, respectively, to train 20 different machine learning (ML) models intended to emulate system behavior. These 20 ML emulators, based on linear methods, Bayesian methods, ensemble learning methods, and multilayer perceptrons (MLPs), were trained to classify the state of mixing and predict three quantities of interest (QoIs) characterizing species production, decay (i.e., average concentration, square of average concentration), and degree of mixing (i.e., variances of species concentration). Unsurprisingly, linear classifiers and regressors failed to reproduce the QoIs; however, ensemble methods (classifiers and regressors) and the MLP model accurately classified the state of reactive mixing and the QoIs. Among ensemble methods, random forest and decision-tree-based AdaBoost faithfully predicted the QoIs. At run time, trained ML emulators produced results times faster than the finite-element simulations. Due to their low computational expense and high accuracy, ensemble and MLP models are excellent emulators for these numerical simulations and great utilities in uncertainty quantification exercises, which can require 1,000s of forward model runs.

97 MATHEMATICS AND COMPUTING↗

Ultrafast Optical Nanoscopy of Carrier Dynamics in Silicon Nanowires

Carrier distribution and dynamics in semiconductor materials often govern their physical properties that are critical to functionalities and performance in industrial applications. The continued miniaturization of electronic and photonic devices calls for tools to probe carrier behavior in semiconductors simultaneously at the picosecond time and nanometer length scales. Here, in this paper, we report pump–probe optical nanoscopy in the visible-near-infrared spectral region to characterize the carrier dynamics in silicon nanostructures. By coupling experiments with the point-dipole model, we resolve the size-dependent photoexcited carrier lifetime in individual silicon nanowires. We further demonstrate local carrier decay time mapping in silicon nanostructures with a sub-50 nm spatial resolution. Our study enables the nanoimaging of ultrafast carrier kinetics, which will find promising applications in the future design of a broad range of electronic, photonic, and optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Behavior of an inversion-based precipitation retrieval algorithm with high-resolution AMPR measurements including a low-frequency 10.7-GHz channel

A microwave-based, profile-type precipitation retrieval algorithm has been used to analyze high-resolution passsive microwave measurements over an ocean background, obtained by the Advanced Microwave Precipitation Radiometer (AMPR) flown on a NASA ER-2 aircraft. The analysis is designed to first determine the improvements that can be gained by adding brightness temperature information from the AMPR low-frequency channel (10.7 GHz) to a multispectral retrieval algorithm nominally run with satellite information at 19, 37, and 85 GHz. The impact of spatial resolution degradation of the high-resolution brightness temperature information on the retrieved rain/cloud liquid water contents and ice water contents is then quantified in order to assess the possible biases inherent to satellite-based retrieval. Careful inspection of the high-resolution aircraft dataset reveals five distinctive brightness temperature features associated with cloud structure and scattering effects that are not generally detectable in current passive microwave satellite measurements. Results suggest that the inclusion of 10.7-GHz information overcomes two basic problems associated with three-channel retrieval. Intercomparisons of retrievals carried out at high-resolution and then averaged to a characteristic satellite scale to the corresponding retrievals in which the brightness temperatures are first convolved down to the satellite scale suggest that with the addition of the 10.7-GHz channel, the rain liquid water contents will not be negatively impacted by special resolution degradation. That is not the case with the ice water contents as they appear ti be quite sensitive to the imposed scale, the implication being that as spatial resolution is reduced, ice water contents will become increasingly underestimated.

Smith, E. A.↗

Anomalous Interlayer Exciton Diffusion in WS 2 /WSe 2 Moiré Heterostructure

Stacking van der Waals crystals allows for the on-demand creation of a periodic potential landscape to tailor the transport of quasiparticle excitations. We investigate the diffusion of photoexcited electron-hole pairs, or excitons, at the interface of WS 2 /WSe 2 van der Waals heterostructure over a wide range of temperatures. We observe the appearance of distinct interlayer excitons for parallel and antiparallel stacking and track their diffusion through spatially and temporally resolved photoluminescence spectroscopy from 30 to 250 K. While the measured exciton diffusivity decreases with temperature, it surprisingly plateaus below 90 K. Our observations cannot be explained by classical models like hopping in the moiré potential. A combination of ab initio theory and molecular dynamics simulations suggests that low-energy phonons arising from the mismatched lattices of moiré heterostructures, also known as phasons, play a key role in describing and understanding this anomalous behavior of exciton diffusion. Our observations indicate that the moiré potential landscape is dynamic down to very low temperatures and that the phason modes can enable efficient transport of energy in the form of excitons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical Control of Dopamine D2-like Receptors with Cell-Specific Fast-Relaxing Photoswitches

Dopamine D2-like receptors (D2R, D3R, and D4R) control diverse physiological and behavioral functions and are important targets for the treatment of a variety of neuropsychiatric disorders. Their complex distribution and activation kinetics in the brain make it difficult to target specific receptor populations with sufficient precision. We describe a new toolkit of light-activatable, fast-relaxing, covalently taggable chemical photoswitches that fully activate, partially activate, or block D2-like receptors. This technology combines the spatiotemporal precision of a photoswitchable ligand (P) with cell type and spatial specificity of a genetically encoded membrane anchoring protein (M) to which the P tethers. These tools set the stage for targeting endogenous D2-like receptor signaling with molecular, cellular, and spatiotemporal precision using only one wavelength of light.

59 BASIC BIOLOGICAL SCIENCES↗

Theory and application of the vector pair correlation function for real-space crystallographic analysis of order/disorder correlations from STEM images

Deviations of local structure and chemistry from the average crystalline unit cell are increasingly recognized to have a significant influence on the properties of many technologically important materials. Here, we present the vector pair correlation function (vPCF) as a new real-space crystallographic analysis method, which can be applied to atomic-resolution scanning transmission electron microscopy (STEM) images to quantify and analyze structural order/disorder correlations. Our STEM-based vPCFs have several advantages over radial PCFs and/or 3D pair distribution functions from x-ray total scattering: vPCFs explicitly retain crystallographic orientation information, are spatially resolved, can be applied directly on a sublattice basis, and are suitable for any material that can be imaged with STEM. To show the utility of our approach, we measure partial vPCFs in Ba 5 SmSn 3 Nb 7 O 30 (BSSN), a tetragonal tungsten bronze (TTB) structured complex oxide. Many TTBs are known to be classical or relaxor ferroelectrics, and these properties have been correlated with the presence of superlattice ordering. BSSN, specifically, exhibits relaxor behavior and an incommensurate structural modulation. From the vPCF data, we observe that, of the cation sites, only the Ba (A2) sublattice is structurally modulated. We then infer the local modulation vector and reveal a marked anisotropy in its correlation length. Finally, short-range correlated polar displacements on the B2 cation sites are observed. This work introduces the vPCF as a powerful real-space crystallography technique, which enables direct, robust quantification of short-to-long range order on a sublattice-specific basis and is applicable to a wide range of complex material types.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flux-based three-dimensional electrodynamic modeling approach to superconducting circuits and materials

Modeling the behavior of superconducting electronic circuits containing Josephson junctions is crucial for the design of superconducting information processors and devices. In this paper, we introduce DEC-QED, a computational approach for modeling the electrodynamics of superconducting electronic circuits containing Josephson junctions in arbitrary three-dimensional electromagnetic environments. DEC-QED captures the nonlinear response and induced currents in BCS superconductors and accurately captures phenomena such as the Meissner effect, flux quantization, and Josephson effects. Using a spatial coarse-graining formulation based on discrete exterior calculus (DEC), DEC-QED can accurately simulate transient and long-time dynamics in superconductors. Finally, the expression of the entire electrodynamic problem in terms of the gauge-invariant flux field and charges makes the resulting classical field theory suitable for second quantization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Unified Interpretation of Variability in Precipitation Isotope Ratios

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation ( δ p ) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δ p within a state-of-the-art climate model and permits a simple decomposition of δ p variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δ p is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δ p and temperature (i.e., the temperature effect). At low latitudes, δ p is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δ p and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance Statement The isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood.

54 ENVIRONMENTAL SCIENCES↗

Center for Frontiers of Subsurface Energy Security (Final Report)

For the past two decades a slowly growing consensus has been that rising temperature is being caused by increases in carbon dioxide (CO 2 ) in the Earth’s atmosphere. What is less consensual is what to do about it. Solutions range from reducing emissions to various ways to capture CO 2 (from effluents of power plants, as plants, etc.) and store it away from the atmosphere. The problem is of such magnitude that it is likely that we will need many methods. Also some methods would cause draconian harm to global economies. This work is about the storage part of the reducing of CO 2 in the atmosphere. There have been many methods proposed for storing CO 2 : in vegetation, at the bottom of oceans, in land farms, and in subsurface formations. The latter is particularly prominent given the large estimated volume in porous formation in the Earth, and the 50-year old experience in injecting CO 2 for enhanced oil recovery. This report is about the science behind subsurface storage, called here geological carbon storage or GCS. Effective GCS requires that billions of metric tons of CO 2 be injected into storage reservoirs annually. GCS feasibility requires balancing the opposing impacts of large emplacement (injection) rates without compromising caprock seal integrity during injection. Once injected, the challenge is to assure the injected CO 2 remains permanently stored. Under most conditions, CO 2 is in a supercritical state, or scCO 2 . scCO 2 is immiscible with the subsurface brine and has a factor of ten smaller viscosity, leading to the development of two-phase fluid flow and scCO 2 bypassing. After the injection of large volumes of scCO 2 , the pore pressure, state of stress, chemical, thermal, and biological steady-state or equilibrium conditions in the subsurface are disrupted, which may lead to unpredictable behavior because the responses to these changes are often non-linear. Current challenges for efficient and reliable scCO 2 storage are: (1) sustaining large injection rates; (2) using available pore space efficiently, and (3) controlling undesired or unexpected behavior, such as scCO 2 leakage. Various aspects of these challenges are addressed by collaborative projects within Center for Frontiers in Subsurface Energy Security (CFSES). Challenge 1 – Sustaining large storage rates. To offset the annual CO 2 emissions of in the United States, ~7 billion metric tons of CO 2 must be injected into the storage reservoirs annually. Injected CO 2 forms a plume that starts spreading, displacing originally resident brine, though inefficiently so. Because of its low viscosity, and buoyant forces, a CO 2 plume rises to the reservoir rock-caprock interface. Injecting large volumes of scCO 2 at sufficiently high rates into subsurface storage formations leads to increases in pore pressures, potential expansion of the reservoir rock, and may result in fracturing of the reservoir rock and/or caprock. CFSES research uses existing and new experimental and modeling approaches to identify chemical-physical controls on the permeability and pore pressure dynamics, anticipating geomechanical (fracturing) events, predicting multi-phase flow patterns and trapping of CO 2 . Challenge 2 – Using pore space with unprecedented efficiency. Since large volumes of scCO 2 are to be stored, the volume available in storage reservoirs must be used efficiently. Storage efficiency is defined as a fraction of pore space occupied by carbon dioxide. Current estimates are that less than 5 percent of available pore volume is available for storage because scCO 2 , having a smaller density and viscosity than reservoir brine, tends to form viscous fingers, and bypass available pore space. This flow regime results in a CO 2 plume spreading over large areas in subsurface. The research goal in Challenge 2 is to advance the fundamental understanding of two-phase flow through porous media, including molecular-to meter- scale experimental and modeling approaches. This work leads to novel strategies to ensure that injected CO 2 occupies more than 5% of the pore space, ideally up to 50%. Challenge 3 – Controlling undesired or unexpected behavior. Following the injection of scCO 2 , the subsurface reservoir re-equilibrates to different physical and chemical states. This re-equilibration in space and time could lead to unexpected and/or undesired behavior: fracturing of reservoir rock and/or caprock, development of preferential flow paths, CO 2 leakage (to the surface or overlaying fresh water reservoirs), induced seismicity, and activation of faults. One of the main research goals of CFSES was to advance the fundamental understanding of how individual chemical and physical processes are coupled. We particularly focused on the chemical-mechanical coupling, and flow-mechanical coupling. We collected experimental and modeling data to determine the temporal and spatial scales of the coupled processes, which may lead to pore collapse caused by creep, activation of fractures and faults, chemically-induced fracture propagation, and self-focusing of scCO 2 flow.

54 ENVIRONMENTAL SCIENCES↗

Effects of the space environment on the health and safety of space workers

Large numbers of individuals are required to work in space to assemble and operate a Solar Power Satellite. The physiological and behavioral consequences for large groups of men and women who perform complex tasks in the vehicular or extravehicular environments over long periods of orbital stay time were considered. The most disturbing consequences of exposure to the null gravity environment found relate to: (1) a generalized cardiovascular deconditioning along with loss of a significant amount of body fluid volume; (2) loss of bone minerals and muscle mass; and (3) degraded performance of neutral mechanisms which govern equilibrium and spatial orientation.

Hull, W. E.↗