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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Landscape Age as a Major Control on the Geography of Soil Weathering

Global-scale models of rock-derived nutrient availability often assume that physical erosion drives soils toward an approximate “steady state” over geologic timescales. By definition, steady-state models do not represent landscape age—that is, the time elapsed since soil formation is initiated by major erosional or depositional events. We hypothesize that this steady-state assumption has large consequences on estimates of soil fertility because landscape age can mediate the retention of mobile elements in soil, particularly in low-relief landscapes and humid climates. We quantified the effect of landscape age on soil fertility by estimating Na retention in soils across the United States and explicitly resolving landscape age in regions that experienced significant deposition or glacial retreat after the Last Glacial Maximum (LGM). We then used a simple one-compartment model to simulate soil formation and weathering, comparing predictions that incorporated landscape age with those based on the steady-state assumption. We found that soils formed in LGM deposits in low-relief, humid settings generally retain 10 times more Na than soils formed outside of LGM deposits. Furthermore, the model that accounted for landscape age outperformed a steady-state model across the United States and increased globally averaged estimates of Na retention by 17%. These results reinforce the idea that landscape age is a major control on weathering and should not be ignored in simulations of nutrient cycling.

58 GEOSCIENCES↗
NASA NTRS1993

Chemical differentiation, thermal evolution, and catastrophic overturn on Venus: Predictions and geologic observations

Observations from Magellan show that: (1) the surface of Venus is generally geologically young, (2) there is no evidence for widespread recent crustal spreading or subduction, (3) the crater population permits the hypothesis that the surface is in production, and (4) relatively few impact craters appear to be embayed by volcanic deposits suggesting that the volcanic flux has drastically decreased as a function of time. These observations have led to consideration of hypotheses suggesting that the geological history of Venus may have changed dramatically as a function of time due to general thermal evolution, and/or thermal and chemical evolution of a depleted mantle layer, perhaps punctuated by catastrophic overturn of upper layers or episodic plate tectonics. We have previously examined the geological implications of some of these models, and here we review the predictions associated with two periods of Venus history. Stationary thick lithosphere and depleted mantle layer, and development of regional to global development of regional to global instabilities, and compare these predictions to the geological characteristics of Venus revealed by Magellan.

Head, James W.↗
DOE OSTI2013

Nuclear Industry Input to the Development of Concepts for the Consolidated Storage of Used Nuclear Fuel - 13411

EnergySolutions and its team partners, NAC International, Exelon Nuclear Partners, Talisman International, TerranearPMC, Booz Allen Hamilton and Sargent and Lundy, have carried out a study to develop concepts for a Consolidated Storage Facility (CSF) for the USA's stocks of commercial Used Nuclear Fuel (UNF), and the packaging and transport provisions required to move the UNF to the CSF. The UNF is currently stored at all 65 operating nuclear reactor sites in the US, and at 10 shutdown sites. The study was funded by the US Department of Energy and followed the recommendations of the Blue Ribbon Commission on America's Nuclear Future (BRC), one of which was that the US should make prompt efforts to develop one or more consolidated storage facilities for commercial UNF. The study showed that viable schemes can be devised to move all UNF and store it at a CSF, but that a range of schemes is required to accommodate the present widely varying UNF storage arrangements. Although most UNF that is currently stored at operating reactor sites is in water-filled pools, a significant amount is now dry stored in concrete casks. At the shutdown sites, the UNF is dry stored at all but two of the ten sites. Various types of UNF dry storage configurations are used at the operating sites and shutdown sites that include vertical storage casks that are also licensed for transportation, vertical casks that are licensed for storage only, and horizontally orientated storage modules. The shutdown sites have limited to nonexistent UNF handling infrastructure and several no longer have railroad connections, complicating UNF handling and transport off the site. However four methods were identified that will satisfactorily retrieve the UNF canisters within the storage casks and transport them to the CSF. The study showed that all of the issues associated with the transportation and storage of UNF from all sites in the US can be accommodated by adopting a staged approach to the construction of the CSF. Stage 1 requires only a cask storage pad and railroad interface to be constructed, and the CSF can then receive the UNF that is in transportable storage casks. Stage 2 adds a canister handling facility, a storage cask fabrication facility and an expanded storage pad, and enables the receipt of all canistered UNF from both operating and shutdown sites. Stage 3 provides a repackaging facility with a water-filled pool that provides flexibility for a range of repackaging scenarios. This includes receiving and repackaging 'bare' UNF into suitable canisters that can be placed into interim storage at the CSF, and enables UNF that is being received, or already in storage onsite, to be repackaged into canisters that are suitable for disposal at a geologic repository. The study used the 'Total System Model' (TSM) to analyze a range of CSF capacities and operating scenarios with differing parameters covering UNF pickup orders, one or more CSF sites, CSF start dates, CSF receipt rates and geologic repository start dates. The TSM was originally developed to model movement of UNF to the Yucca Mountain repository and was modified for this study to enable the CSF to become the 'gateway' to a future geologic repository. The TSM analysis enabled costs to be estimated for each scenario and showed how these are influenced by each of the parameters. This information will provide essential underpinning for a future Conceptual Design preparation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Development of a discontinuous approach for modeling fluid flow in heterogeneous media using the numerical manifold method

Summary In the numerical modeling of fluid flow in heterogeneous geological media, large material contrasts associated with complexly intersected material interfaces are challenging, not only related to mesh discretization but also for the accurate realization of the corresponding boundary constraints. To address these challenges, we developed a discontinuous approach for modeling fluid flow in heterogeneous media using the numerical manifold method (NMM) and the Lagrange multiplier method (LMM) for modeling boundary constraints. The advantages of NMM include meshing efficiency with fixed mathematical grids (covers), the convenience of increasing the approximation precision, and the high integration precision provided by simplex integration. In this discontinuous approach, the elements intersected by material interfaces are divided into different elements and linked together using the LMM. We derive and compare different forms of LMMs and arrive at a new LMM that is efficient in terms of not requiring additional Lagrange multiplier topology, yet stringently derived by physical principles, and accurate in numerical performance. To demonstrate the accuracy and efficiency of the NMM with the developed LMM for boundary constraints, we simulate a number of verification and demonstration examples, involving a Dirichlet boundary condition and dense and intersected material interfaces. Last, we applied the developed model for modeling fluid flow in heterogeneous media with several material zones containing a fault and an opening. We show that the developed discontinuous approach is very suitable for modeling fluid flow in strongly heterogeneous media with good accuracy for large material contrasts, complex Dirichlet boundary conditions, or complexly intersected material interfaces. Copyright © 2015 John Wiley & Sons, Ltd.

Hu, Mengsu↗
DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Pliocene Model Intercomparison (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP operates under the umbrella of the Palaeoclimate Modelling Intercomparison Project (PMIP), which examines multiple intervals in Earth history, the consistency of model predictions in simulating these intervals and their ability to reproduce climate signals preserved in geological climate archives. This paper provides a thorough model intercomparison project description, and documents the experimental design in a detailed way. Specifically, this paper describes the experimental design and boundary conditions that will be utilized for the experiments in Phase 2 of PlioMIP.

climate change↗
DOE OSTI2019

Generation of synthetic dielectric dispersion logs in organic-rich shale formations using neural-network models

Dielectric dispersion (DD) logs acquired in subsurface geologic formations generally are composed of conductivity ([Formula: see text]) and relative permittivity ([Formula: see text]) measurements at four discrete frequencies in the range of 10 MHz to 1 GHz. Acquisition of DD logs in subsurface formations is operationally challenging, and it requires a hard-to-deploy infrastructure. We developed three supervised neural-network-based predictive methods to process conventional, easy-to-acquire subsurface logs for generating the eight DD logs acquired at four frequencies. These predictive methods will improve reservoir characterization in the absence of a DD logging tool. The predictive methods are tested in three wells intersecting organic-rich shale formations of the Permian Basin and the Bakken Shale. The first method predicts the eight dispersion logs simultaneously using a single artificial neural network (ANN) model, whereas the second method simultaneously predicts the four conductivity dispersion logs using one ANN model, followed by simultaneous prediction of four permittivity dispersion logs using a second ANN model. The third method sequentially predicts the eight dispersion logs, one at a time using eight sequential ANN models, based on a predetermined ranking of the prediction accuracy for each of the eight DD logs when simultaneously generated. Considering that the conventional and DD logs are recorded more than 10,000 ft deep in the subsurface using logging tools that are run at different times in rugose boreholes for sensing the near-wellbore geologic formation, the data used in this predictive work is prone to noise and biases that tend to adversely affect the prediction performances of the proposed methods. In terms of normalized root-mean square error (Nrms error), the prediction performances of the second predictive method are 8.5% worse and 6.2% better for the conductivity and permittivity dispersion logs, respectively, as compared with those of the first predictive method. The third method has best prediction performance for permittivity dispersion logs, which is 0.089 in terms of the Nrms error.

Geochemistry & Geophysics↗
DOE OSTI2018

Comparative modelling of the coupled thermal–hydraulic-mechanical (THM) processes in a heated bentonite pellet column with hydration

For the deep geological disposal of high-level radioactive waste in argillaceous rocks, the heat production of the waste is an important driver for thermal–hydraulic-mechanical (THM)-coupled processes. These THM processes influence the properties and conditions of the near field that in many repository designs contains bentonite as a clay buffer. One task in the DECOVALEX-2015 (DEvelopment of COupled models and their VALidation against Experiments) project was the modelling of a heated bentonite column (Villar et al. in Long-term THM tests reports: THM cells for the HE-E test: update of results until February 2014. Deliverable-no: D2.2-7.3. CIEMAT Technical Report IEMAT/DMA/2G210/03/2014, 2014) in preparation for the in situ heater experiment HE-E at the underground rock laboratory Mont Terri. DECOVALEX is an international cooperative project that focuses on the development and validation of mathematical models for simulating such coupled processes associated with disposal in deep geological repositories. Eight modelling teams developed their own THM-coupled models for the bentonite column experiment, using six different simulation codes. Each of the teams individually calibrated the THM parameters for the bentonite material. The eight resulting parameter sets agree well and allow a satisfactory reproduction of the TH measurements by all models. The modelling results for the evolution of temperature and relative humidity over time at three sensors in the bentonite column are in good agreement between the teams and with the measured data. Also, changes of the temperature due to modifications of the insulation and the adjustment of the heating power during the course of the experiment are well reproduced. The models were thus able to reproduce the main physical processes of the experiment, both for vapour-dominated diffusion during the heating phase and combined liquid and vapour transport during a subsequent heating and hydration phase. Lastly, based on the parameter sets, the teams predict a penetration of the water infiltration front in the 48-cm column filled with bentonite pellets to a depth between 25 and 35 cm over the 15,000 h (i.e. over 20 months) of the hydration phase of the experiment.

58 GEOSCIENCES↗
DOE OSTI2014

Monitoring CO 2 sequestration into deep saline aquifer and associated salt intrusion using coupled multiphase flow modeling and time lapse electrical resistivity tomography

Successful geological storage and sequestration of carbon dioxide (CO2) require efficient monitoring of the migration of CO2 plume during and after large-scale injection in order to verify the containment of the injected CO2 within the target formation and to evaluate potential leakage risk. Field studies have shown that surface and cross-borehole electrical resistivity tomography (ERT) can be a useful tool in imaging and characterizing solute transport in heterogeneous subsurface. In this synthetic study, we have coupled a 3-D multiphase flow model with a parallel 3-D time-lapse ERT inversion code to explore the feasibility of using time-lapse ERT for simultaneously monitoring the migration of CO2 plume in deep saline formation and potential brine intrusion into shallow fresh water aquifer. Direct comparisons of the inverted CO2 plumes resulting from ERT with multiphase flow simulation results indicate the ERT could be used to delineate the migration of CO2 plume. Detailed comparisons on the locations, sizes and shapes of CO2 plume and intruded brine plumes suggest that ERT inversion tends to underestimate the area review of the CO2 plume, but overestimate the thickness and total volume of the CO2 plume. The total volume of intruded brine plumes is overestimated as well. However, all discrepancies remain within reasonable ranges. Our study suggests that time-lapse ERT is a useful monitoring tool in characterizing the movement of injected CO2 into deep saline aquifer and detecting potential brine intrusion under large-scale field injection conditions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗
DOE OSTI2013

Diffusion Dominant Solute Transport Modelling In Deep Repository Under The Effect of Emplacement Media Degradation - 13285

Deep geologic disposal of high activity and long-lived radioactive waste is being actively considered and pursued in many countries, where low permeability geological formations are used to provide long term waste contaminant with minimum impact to the environment and risk to the biosphere. A multi-barrier approach that makes use of both engineered and natural barriers (i.e. geological formations) is often used to further enhance the containment performance of the repository. As the deep repository system subjects to a variety of thermo-hydro-chemo-mechanical (THCM) effects over its long 'operational' lifespan (e.g. 0.1 to 1.0 million years, the integrity of the barrier system will decrease over time (e.g. fracturing in rock or clay)). This is broadly referred as media degradation in the present study. This modelling study examines the effects of media degradation on diffusion dominant solute transport in fractured media that are typical of deep geological environment. In particular, reactive solute transport through fractured media is studied using a 2-D model, that considers advection and diffusion, to explore the coupled effects of kinetic and equilibrium chemical processes, while the effects of degradation is studied using a pore network model that considers the media diffusivity and network changes. Model results are presented to demonstrate the use of a 3D pore-network model, using a novel architecture, to calculate macroscopic properties of the medium such as diffusivity, subject to pore space changes as the media degrade. Results from a reactive transport model of a representative geological waste disposal package are also presented to demonstrate the effect of media property change on the solute migration behaviour, illustrating the complex interplay between kinetic biogeochemical processes and diffusion dominant transport. The initial modelling results demonstrate the feasibility of a coupled modelling approach (using pore-network model and reactive transport model) to examine the long term behaviour of deep geological repositories with media property change under complex geochemical conditions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Constraints on Climate and Habitability for Earth-like Exoplanets Determined from a General Circulation Model

Conventional definitions of habitability require abundant liquid surface water to exist continuously over geologic timescales. Water in each of its thermodynamic phases interacts with solar and thermal radiation and is the cause for strong climatic feedbacks. Thus, assessments of the habitable zone require models to include a complete treatment of the hydrological cycle over geologic time. Here, we use the Community Atmosphere Model from the National Center for Atmospheric Research to study the evolution of climate for an Earth-like planet at constant CO{sub 2}, under a wide range of stellar fluxes from F-, G-, and K-dwarf main sequence stars. Around each star we find four stable climate states defined by mutually exclusive global mean surface temperatures ( T {sub s}); snowball ( T {sub s} ≤ 235 K), waterbelt (235 K ≤ T {sub s} ≤ 250 K), temperate (275 K ≤ T {sub s} ≤ 315 K), and moist greenhouse ( T {sub s} ≥ 330 K). Each is separated by abrupt climatic transitions. Waterbelt, temperate, and cooler moist greenhouse climates can maintain open-ocean against both sea ice albedo and hydrogen escape processes respectively, and thus constitute habitable worlds. We consider the warmest possible habitable planet as having T {sub s} ∼ 355 K, at which point diffusion limited water-loss could remove an Earth ocean in ∼1 Gyr. Without long timescale regulation of non-condensable greenhouse species at Earth-like temperatures and pressures, such as CO{sub 2}, habitability can be maintained for an upper limit of ∼2.2, ∼2.4, and ∼4.7 Gyr around F-, G-, and K-dwarf stars respectively, due to main sequence brightening.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Constraints on Climate and Habitability for Earth-like Exoplanets Determined from a General Circulation Model

Conventional definitions of habitability require abundant liquid surface water to exist continuously over geologic timescales. Water in each of its thermodynamic phases interacts with solar and thermal radiation and is the cause for strong climatic feedbacks. Thus, assessments of the habitable zone require models to include a complete treatment of the hydrological cycle over geologic time. Here, we use the Community Atmosphere Model from the National Center for Atmospheric Research to study the evolution of climate for an Earth-like planet at constant CO2, under a wide range of stellar fluxes from F-, G-, and K-dwarf main sequence stars. Around each star we find four stable climate states defined by mutually exclusive global mean surface temperatures (Ts); snowball (Ts ≤ 235 K), waterbelt (235 K ≤ Ts ≤ 250 K), temperate (275 K ≤ Ts ≤ 315 K), and moist greenhouse (Ts ≥ 330 K). Each is separated by abrupt climatic transitions. Waterbelt, temperate, and cooler moist greenhouse climates can maintain open-ocean against both sea ice albedo and hydrogen escape processes respectively, and thus constitute habitable worlds. We consider the warmest possible habitable planet as having Ts ∼ 355 K, at which point diffusion limited water-loss could remove an Earth ocean in ∼1 Gyr. Without long timescale regulation of non-condensable greenhouse species at Earth-like temperatures and pressures, such as CO2, habitability can be maintained for an upper limit of ∼2.2, ∼2.4, and ∼4.7 Gyr around F-, G-, and K-dwarf stars respectively, due to main sequence brightening.

Eric T Wolf↗
NASA NTRS2017

Constraints on Climate and Habitability for Earth-like Exoplanets Determined from a General Circulation Model

Conventional definitions of habitability require abundant liquid surface water to exist continuously over geologic timescales. Water in each of its thermodynamic phases interacts with solar and thermal radiation and is the cause for strong climatic feedbacks. Thus, assessments of the habitable zone require models to include a complete treatment of the hydrological cycle over geologic time. Here, we use the Community Atmosphere Model from the National Center for Atmospheric Research to study the evolution of climate for an Earth-like planet at constant CO2, under a wide range of stellar fluxes from F-, G-, and K-dwarf main sequence stars. Around each star we find four stable climate states defined by mutually exclusive global mean surface temperatures (T(sub s)); snowball (T(sub s) ≼ 235 K), waterbelt (235 K ≼ T(sub s) ≼ 250 K), temperate (275 K ≼ T(sub s) ≼ 315 K), and moist greenhouse (T(sub s) ≽ 330 K). Each is separated by abrupt climatic transitions. Waterbelt, temperate, and cooler moist greenhouse climates can maintain open-ocean against both sea ice albedo and hydrogen escape processes respectively, and thus constitute habitable worlds. We consider the warmest possible habitable planet as having T(sub s) ∼ 355 K, at which point diffusion limited water-loss could remove an Earth ocean in ∼1 Gyr. Without long timescale regulation of non-condensable greenhouse species at Earth-like temperatures and pressures, such as CO2, habitability can be maintained for an upper limit of ∼2.2, ∼2.4, and ∼4.7 Gyr around F-, G-, and K-dwarf stars respectively, due to main sequence brightening.

Astrobiology↗
DOE OSTI2024

Offshore application of landslide susceptibility mapping using gradient-boosted decision trees: a Gulf of Mexico case study

Abstract Among natural hazards occurring offshore, submarine landslides pose a significant risk to offshore infrastructure installations attached to the seafloor. With the offshore being important for current and future energy production, there is a need to anticipate where future landslide events are likely to occur to support planning and development projects. Using the northern Gulf of Mexico (GoM) as a case study, this paper performs Landslide Susceptibility Mapping (LSM) using a gradient-boosted decision tree (GBDT) model to characterize the spatial patterns of submarine landslide probability over the United States Exclusive Economic Zone (EEZ) where water depths are greater than 120 m. With known spatial extents of historic submarine landslides and a Geographic Information System (GIS) database of known topographical, geomorphological, geological, and geochemical factors, the resulting model was capable of accurately forecasting potential locations of sediment instability. Results of a permutation modelling approach indicated that LSM accuracy is sensitive to the number of unique training locations with model accuracy becoming more stable as the number of training regions was increased. The influence that each input feature had on predicting landslide susceptibility was evaluated using the SHapely Additive exPlanations (SHAP) feature attribution method. Areas of high and very high susceptibility were associated with steep terrain including salt basins and escarpments. This case study serves as an initial assessment of the machine learning (ML) capabilities for producing accurate submarine landslide susceptibility maps given the current state of available natural hazard-related datasets and conveys both successes and limitations.

Dyer, Alec S. (ORCID:0000000219813904)↗
NASA NTRSDate not supplied

Geologic Maps for Civil Engineering and Infrastructure Planning

The Artemis Program mandate for sustainable, long-term presence on the Moon requires learning to "Live Off the Land". Geologic maps enable a paradigm shift to model the development and scaling of infrastructure for robotic and human exploration inside a bounded system on the lunar surface. Relying on geologic maps produced from orbital data and robotic precursor missions, in-situ resource utilization (ISRU) will be required to produce infrastructure, building materials and consumables. The ISRU value chain must be mapped to identify linkages of resources, producers, processes and equipment capabilities for transforming excavated regolith into usable feedstocks. Coordination will be required to balance supply and demand across the whole system of lunar infrastructure and operations, at each stage of development.

Geologic Mapping↗
DOE OSTI2013

Volumetric Properties and Fluid Phase Equilibria of CO2 + H2O

The need for accurate modeling of fluid-mineral processes over wide ranges of temperature, pressure and composition highlighted considerable uncertainties of available property data and equations of state, even for the CO2 + H2O binary system. In particular, the solubility, activity, and ionic dissociation equilibrium data for the CO2-rich phase, which are essential for understanding dissolution/precipitation, fluid-matrix reactions, and solute transport, are uncertain or missing. In this paper we report the results of a new experimental study of volumetric and phase equilibrium properties of CO2 + H2O, to be followed by measurements for bulk and confined multicomponent fluid mixtures. Mixture densities were measured by vibrating tube densimetry (VTD) over the entire composition range at T = 200 and 250 C and P = 20, 40, 60, and 80 MPa. Initial analysis of the mutual solubilities, determined from volumetric data, shows good agreement with earlier results for the aqueous phase, but finds that the data of Takenouchi and Kennedy (1964) significantly overestimated the solubility of water in supercritical CO2 (by a factor of more than two at 200 C). Resolving this well-known discrepancy will have a direct impact on the accuracy of predictive modeling of CO2 injection in geothermal reservoirs and geological carbon sequestration through improved equations of state, needed for calibration of predictive molecular-scale models and large-scale reactive transport simulations.

Capobianco, Ryan↗
NASA NTRS1990

Lakshmi Planum, Venus - Characteristics and models of origin

The distinctive and unique Venusian geological structure, Lakshmi Planum, is an expansive relatively smooth flat plateau containing two large shield volcanos and abundant volcanic plains in the midst of a region of extreme relief. The characteristics which distinguish Lakshmi from other volcanic regions known on the planet, such as Beta Regio, are identified. These include its high altitude and plateaulike nature; the presence of two very large low shield structures with distinctive central paterae and long radiating flows; and its compressional tectonic environment. The detailed nature and significance of the volcanic deposits on Lakshmi are determined; the erruption styles and conditions are interpreted; and the link between the observed volcanism and tectonic environment of the region is discussed. Models for the formation of Lakshmi Planum are presented and evaluated.

Roberts, Kari M.↗