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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗
DOE OSTI2025

COMPUTATION FLUID DYNAMICS ANALYSIS FOR GENERIC SMALL MODULAR REACTOR CONTAINMENT SEPARATE EFFECTS TEST

It is desirable for fourth-generation Small Modular Reactors to be passively cooled in standard and accident operations. Passive Containment Cooling Systems can reject heat from the containment structure, without using pumps or blowers. The targeted design containment structure is a large, domed, stainless steel, cylindrical vessel. In a postulated Design Basis Accident, steam will flash inside containment. Steam condensation occurs on the inner containment wall and transfers heat through the steel containment into a large body of water known as the annular reservoir (AR) surrounding the vessel serving as the ultimate heat sink. Natural circulation drives the flow in the AR and heat will be released to the environment by evaporation of water. Unique containment geometry requires a separate effects test (SET) facility for the verification and validation of the computer code and evaluation model development and assessment for reactor licensing efforts. In this study, STAR-CCM+, a computational fluid dynamics (CFD) code was used to inform the decision-making process on the design of the SET. The CFD simulation modeled, a two-phase turbulent flow with fluid film development and heat transfer for different containment geometries. The Reactor Excursion and Leak Analysis Program will also be used in a code-to-code verification against the CFD results.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRS1994

Hubble Space Telescope observations of planetary nebulae in the magellanic clouds. 2: SMP 85, a young planetary

We have obtained Hubble Space Telescope Planetary Camera images in the (O III) lambda 5007 A emission line, and Faint Object Spectrograph (FOS) UV spectrophotometry of the low-excitation planetary nebula SMP 85 in the Large Magellanic Cloud. By combining these results with existing optical spectrophotometry, absolute flux measurements, and dynamical and density information, we have been able to construct a fully self-consistent nebular model. This proves that SMP 85 is a dense, young, carbon-rich object which started to be ionized about 500-1000 years ago, and which contains a substantial inner reservoir of atomic or molecular gas, probably in the form of many small cloudlets. These cloudlets have been ejected at a velocity not exceeding 6 km/s, a result which, together with the morphology is an important clue to mass loss during late asymptotic giant branch (AGB) evolution. We have directly detected the central star through its UV continuum emission, and from both Zanstra techniques and nebular modeling derive a stellar temperature of 46000 +/- 2000 K, a stellar luminosity of 7300 +/- 700 solar luminosity, and a core mass of 0.63-0.67 solar mass. The nebular analysis also demonstrates that there is severe depletion of the nebular gases onto dust grains, most likely of the calcium magnesium silicate variety; a surprising result in view of the carbon-rich nature of the ionized nebula.

Dopita, Michael A.↗
NASA NTRS2004

High Silicate Crystalline-to-Amorphous Ratios in Comets C/2001 Q4 (NEAT) and Hale-Bopp

Crystalline silicates, by their apparent absence in the ISM, are dust grains that experienced high temperatures in the solar nebula. Mg-rich crystalline silicates formed either by condensation from hot nebular gases (1450 K) or by the annealing of Mg-rich amorphous silicates (approximately 1000 K) in shocks in the 5-10AU region or by radial transport into and out of the hot inner zones, e.g., T(sub d) greater than 1000K at r(sub h) less than 5AU, 10(exp -6) -10(exp -5) solar mass per year, alpha = 10(exp -4) of the early solar nebula. Mg-rich crystalline silicates are found in interplanetary dust particles (IDPs) and produce IR spectral features in many Oort cloud comets. In May 2004, we discovered strong crystalline silicate features in the dynamically new Oort cloud comet C/2001 Q4 (NEAT). Thermal emission modeling of comets Q4 and C/1995 O1 (Hale-Bopp) demonstrate that both these comets have similar, high silicate crystalline-toamorphous ratios of 2.4 and 2.1, respectively, indicating that these icy planetesimals aggregated from similar reservoirs of material or that crystalline silicates were widely distributed within the comet-forming zone. This argues for efficient annealing mechanisms and radial mixing.

Wooden, D. H.↗
NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗
NASA NTRS2004

High Silicate Crystalline-to-Amorphous Ratios in Comets C/2001 Q4 (NEAT) and Hale-Bopp

Crystalline silicates, by their apparent absence in the ISM, are dust grains that experienced high temperatures in the solar nebula. Mg-rich crystalline silicates formed either by condensation from hot nebular gases (1450 K) or by the annealing of Mg-rich amorphous silicates (approx. 1000 K) in shocks in the 5-10 AU region or by radial transport into and out of the hot inner zones, e.g., T(sub d) > 1000 K at r(sub h) < 5 AU, 10(exp -6) - 10(exp -5) M(sub O)/yr, alpha = 10(exp -4) of the early solar nebula. Mg-rich crystalline silicates are found in interplanetary dust particles (IDPs) and produce IR spectral features in many Oort cloud comets. In May 2004, we discovered strong crystalline silicate features in the dynamically new Oort cloud comet C/2001 Q4 (NEAT). Thermal emission modeling of comets Q4 and C/1995 O1 (Hale-Bopp) demonstrate that both these comets have similar, high silicate crystalline-to-amorphous ratios of 2.4 and 2.1, respectively, indicating that these icy planetesimals aggregated from similar reservoirs of material or that crystalline silicates were widely distributed within the comet-forming zone. This argues for efficient annealing mechanisms and radial mixing.

Wooden, D. H.↗
DOE OSTI2025

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗
NASA NTRS2015

Pyrotechnically Actuated Gas Generator Utilizing Aqueous Methanol

A gas-generating device was developed to supplement the ram-air inflation of a supersonic ballute. The device is designed to initially pressurize the ballute following deployment, exposing and orienting its ram-air inlets to free-stream air for complete inflation. The supplemental pressurization decreases the total inflation time, and increases the likelihood of a successful inflation. The device contains a reservoir filled with an aqueous mixture of methanol that, when released in to the interior of the ballute, rapidly vaporizes due to the low ambient pressure. Upon activation of the device, a pair of redundant ring mechanisms initiate pyrotechnic charges that pressurize and rupture the reservoir, resulting in ejection of the methanol in to the ballute. In addition to its role in inflation, the device serves as the structural connection to the ballute. Analytical models were developed for the inflation capability of the device, which were verified using vacuum chamber testing of developmental hardware. Static, deployment, and environmental testing demonstrated the functionality of the ring mechanism and reservoir under several temperature and pressure conditions. Finally, the device was successfully operated during the first Supersonic Flight Dynamics Test (SFDT) of NASA's Low Density Supersonic Decelerator (LDSD) project. The design architecture is scalable to accommodate different quantities of gas generation, can be adjusted to operate in a variety of temperature and atmospheric pressure regimes, and provides a robust device that may be installed with minimal risk to personnel or hardware.

IA↗
DOE OSTI2026

Dynamically reconfigurable topological routing in nonlinear photonic systems

The propagation path of topologically protected states is bound to the interface between regions with different topology, and as such, the functionality of linear photonic devices leveraging these states is fixed during fabrication. Here, we propose a mechanism for dynamic control over a driven dissipative system’s local topology, yielding reconfigurable topological interfaces and thus tunable paths for protected routing. We illustrate our approach in non-resonantly pumped polariton lattices, where the nonlinear interaction between the polaritons and the exciton reservoir due to non-resonant pumping can yield picosecond-scale changes in the propagation paths of the chiral edge states. To analytically confirm the numerically observed topological dynamics, we generalize the spectral localizer framework to non-linear non-Hermitian Chern materials and apply this framework to a continuous model of the polariton system based on a driven-dissipative Gross-Pitaevskii equation. In doing so, we show that the local changes in the polariton lattice’s topology are captured by a local Chern marker. Looking forward, we anticipate such reconfigurable topological routing will enable the realization of novel classes of topological photonic devices.

Wong, Stephan [Sandia National Laboratories (SNL-N↗
DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗
DOE OSTI2026

Analytic rate theory of polariton relaxation that explains long polariton lifetime

Hybridization of a molecular exciton with a quantized photon creates a polariton. Despite extensive experimental investigations, the apparent lifetime of the exciton–polariton is not well-understood. For this work, we examined the steady-state population dynamics for a Holstein–Tavis–Cumming Hamiltonian to illuminate the long-term polaritonic dynamics and lifetime of the exciton–polariton in an optical cavity. For a realistic description of polariton relaxation, cavity loss and various exciton decay channels are included in the model. We found that in the presence of weak but finite exciton loss, the apparent lifetime of the lower polariton coincides with the out-of-cavity exciton lifetime and is independent of cavity-matter detuning. This is a simple explanation for the experimentally observed lifetimes for exciton polaritons and theoretically justifies the dark state reservoir hypothesis. Furthermore, if the upper polariton is initially populated, the system reaches the steady state very quickly, leading to single-exponential polariton relaxation. Starting from the lower polariton leads to a longer pre-steady-state time period, leading to double-exponential relaxation. Finally, we considered the effect of site orientational disorders and the exciton frequency disorderers. Under the collective limit, the effects of this disorder can be included in Fermi’s golden rule population dynamics without explicit sampling. For the exciton energy disorders, numerical calculations are needed. Our theoretical framework is applicable to interpret exciton–polariton experiments, especially related to the measured apparent lifetime of polaritons.

Chemical dynamics↗
DOE OSTI2024

Pore‐Scale Modeling of Carbon Dioxide and Hydrogen Transport During Geologic Gas Storage

Abstract Geologic storage of CO 2 and H 2 are climate‐positive techniques for meeting the energy transition. While similar formations could be considered for both gases, the flow dynamics could differ due to differences in their thermophysical properties. We conduct a rigorous pore‐scale study of water/CO 2 and water/H 2 systems at relevant reservoir conditions in a Bentheimer rock sample using the lattice Boltzmann method to quantify the effects of capillary, viscous, inertial, and wetting forces during gas invasion. At similar conditions, H 2 invasion is weaker compared to CO 2 due to unfavorable viscosity ratios. Increasing flow rate, however, increases the breakthrough saturation for both gas systems in the range of capillary numbers studied. At isolated conditions of flow rate, viscosity ratio, and wettability, local inertial effects are found to be critical and show consistent increase in the invaded gas saturation. The effect of inertial forces persits for both gases across all field conditions tested.

58 GEOSCIENCES↗
DOE OSTI2024

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗
DOE OSTI2025

Echo state network for coarsening dynamics of charge density waves

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer. Compared with other recurrent neural networks, one great advantage of ESN is the simplicity of its training process. Yet, despite the seemingly restricted learnable parameters, ESN has been shown to successfully capture the spatial-temporal dynamics of complex patterns. Here we build an ESN to model the coarsening dynamics of charge-density waves (CDWs) in a semiclassical Holstein model, which exhibits a checkerboard electron density modulation at half-filling stabilized by a commensurate lattice distortion. The inputs to the ESN are local CDW order parameters in a finite neighborhood centered around a given site, while the output is the predicted CDW order of the center site at the next time step. Special care is taken in the design of couplings between hidden layer and input nodes to ensure lattice symmetries are properly incorporated into the ESN model. Since the model predictions depend only on CDW configurations of a finite domain, the ESN is scalable and transferrable in the sense that a model trained on dataset from a small system can be directly applied to dynamical simulations on larger lattices. Furthermore, our work opens avenues for efficient dynamical modeling of pattern formations in functional electron materials.

2-dimensional systems↗
DOE OSTI2025

Simulation insights into wetting properties of hydrogen-brine-clay for hydrogen geo-storage

Hydrogen geo-storage is attracting substantial interdisciplinary interest as a cost-effective and sustainable option for medium- and long-term storage. Hydrogen can be stored underground in diverse formations, including aquifers, salt caverns, and depleted oil and gas reservoirs. The wetting dynamics of the hydrogen-brine-rock system are critical for assessing both structural and residual storage capacities, and ensuring containment safety. Through molecular dynamics simulations, we explore how varying concentrations of cushion gases (CO 2 or CH 4 ) influence the wetting properties of hydrogen-brine-clay systems under geological conditions (15 MPa and 333 K). We employed models of talc and the hydroxylated basal face of kaolinite (kaoOH) as clay substrates. Our findings reveal that the effect of cushion gases on hydrogen-brine-clay wettability is strongly dependent on the clay-brine interactions. Notably, CO 2 and CH 4 reduce the water wettability of talc in hydrogen-brine-talc systems, while exerting no influence on the wettability of hydrogen-brine-kaoOH systems. Detailed analysis of free energy of cavity formation near clay surfaces, clay-brine interfacial tensions, and the Willard-Chandler surface for gas-brine interfaces elucidate the molecular mechanisms underlying wettability changes. Our simulations identify empirical correlations between wetting properties and the average free energy required to perturb a flat interface when clay-brine interactions are less dominant. Here, our thorough thermodynamic analysis of rock-fluid and fluid-fluid interactions, aligning with key experimental observations, underscores the utility of simulated interfacial properties in refining contact angle measurements and predicting experimentally relevant properties. These insights significantly enhance the assessment of gas geo-storage potential. Prospectively, the approaches and findings obtained from this study could form a basis for more advanced multiscale simulations that consider a range of geological and operational variables, potentially guiding the development and improvement of geo-storage systems in general, with a particular focus on hydrogen storage.

25 ENERGY STORAGE↗
NASA NTRS2024

The dynamical origins of the dark comets and a proposed evolutionary track

So-called ‘dark comets’ are small, morphologically inactive near-Earth objects (NEOs) that exhibit nongravitational accelerations inconsistent with radiative effects. These objects exhibit short rotational periods (minutes to hours), where measured. We find that the strengths required to prevent catastrophic disintegration are consistent with those measured in cometary nuclei and expected in rubble pile objects. We hypothesize that these dark comets are the end result of a rotational fragmentation cascade, which is consistent with their measured physical properties. We calculate the predicted size-frequency distribution for objects evolving under this model. Using dynamical simulations, we further demonstrate that the majority of these bodies originated from the 𝜈6 resonance, implying the existence of volatiles in the current inner main belt. Moreover, one of the dark comets, (523599) 2003 RM, likely originated from the outer main belt, although a JFC origin is also plausible. These results provide strong evidence that volatiles from a reservoir in the inner main belt are present in the near-Earth environment.

Aster G Taylor↗
NASA NTRS1976

Analysis of information systems for hydropower operations: Executive summary

An analysis was performed of the operations of hydropower systems, with emphasis on water resource management, to determine how aerospace derived information system technologies can effectively increase energy output. Better utilization of water resources was sought through improved reservoir inflow forecasting based on use of hydrometeorologic information systems with new or improved sensors, satellite data relay systems, and use of advanced scheduling techniques for water release. Specific mechanisms for increased energy output were determined, principally the use of more timely and accurate short term (0-7 days) inflow information to reduce spillage caused by unanticipated dynamic high inflow events. The hydrometeorologic models used in predicting inflows were examined in detail to determine the sensitivity of inflow prediction accuracy to the many variables employed in the models, and the results were used to establish information system requirements. Sensor and data handling system capabilities were reviewed and compared to the requirements, and an improved information system concept was outlined.

Sohn, R. L.↗