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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

life support↗
DOE OSTI2022

The impact of agricultural trade approaches on global economic modeling

Future socioeconomic and climate scenarios have been explored using integrated assessment models (IAMs) to understand interactions between human development and global environmental change in the long run. However, differences in trade modeling approaches are an important source of uncertainty in the assessments, particularly for regional projections. Here, we explore the critical role of trade modeling in assessing the potential future of global agroeconomics and terrestrial carbon emissions with a well-established IAM, the Global Change Assessment Model (GCAM). We update the crop trade modeling framework in GCAM from a Heckscher-Ohlin-Vanek (HOV) structure with integrated world markets (IWM) to a newly developed logit-based Armington approach with segmented regional markets (SRM). The updates make it possible to study the sensitivity of model projections of future agroeconomics and terrestrial carbon emissions to assumptions of the state and magnitude of global market integration. Our results demonstrate that assuming full global market integration, represented by homogeneous product modeling, neglecting economic geography, and excluding margins and tariffs, could lead to lower cropland use (i.e., by 115 million hectares globally) and terrestrial carbon fluxes (i.e., by 25%) by the end of the century. However, the results are highly heterogeneous across regions with more pronounced regional trade responses driven by global market integration. Our study highlights the critical role of trade modeling around product differentiation, economic geography, and regional trade parameterization in global economic or integrated assessment modeling. The results also imply that further reconciliations in trade model approaches could improve the convergence of regional results among models in model intercomparison studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗
NASA NTRS2021

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗
NASA NTRSDate not supplied

Updated Analysis of the Trash Compaction and Processing System: Water Collected from Trash, Evaluation of the Source Contaminant Control System, and Zotek® F30 Foam Processing

The Trash Compaction and Processing System (TCPS) aims to reduce volume, biologically safen, physically stabilize, manage effluents, and recover resources from astronaut trash in the International Space Station (ISS). At NASA Ames Research Center (ARC), there are two test systems: the Heat Melt Compactor (HMC), which compacts the trash into a tile with temperature and pressure, and the Source Contaminant Control System (SCCS), which is the gas management subsystem aimed to reduce contaminants by converting them into carbon dioxide (CO 2 ) and water (H 2 O) vapor. Both the HMC and SCCS serve as test systems that support TCPS development by conducting risk reduction activities associated with an ISS technology demonstration. In this paper, the risk reduction activities discussed are the testing of different trash models for operational scenarios in the HMC, investigating the water extracted from those trash models, and managing the gaseous effluents from the trash via contaminant conversion through the SCCS. The HMC has undergone several tests of different trash models and cases in which a containment bag is used or not. For the first topic, this paper will analyze the water collected and recovered from these tests and analyze the effect of specific trash containment bags. For the second topic, this paper will individually evaluate the carbon bed and catalytic oxidizer (CatOx) to understand what components the carbon bed removes and what contaminants are converted in the CatOx. For the third and final topic, this paper will discuss Zotek® F30 foam processing in the HMC unit and testing verification in correlation to defined TCPS requirements. A foam model was added to reduce the volume of foam that take up space in the ISS. Overall, this paper is a compilation and an updated analysis of tests conducted in the lab-scale TCPS at ARC within the past year.

TCPS↗
DOE OSTI2021

Fast inversion, preconditioned quantum linear system solvers, fast Green's-function computation, and fast evaluation of matrix functions

Preconditioning is the most widely used and effective way for treating ill-conditioned linear systems in the context of classical iterative linear system solvers. We introduce a quantum primitive called fast inversion, which can be used as a preconditioner for solving quantum linear systems. The key idea of fast inversion is to directly block encode a matrix inverse through a quantum circuit implementing the inversion of eigenvalues via classical arithmetics. We demonstrate the application of preconditioned linear system solvers for computing single-particle Green's functions of quantum many-body systems, which are widely used in quantum physics, chemistry, and materials science. We analyze the complexities in three scenarios: the Hubbard model, the quantum many-body Hamiltonian in the plane-wave-dual basis, and the Schwinger model. We also provide a method for performing Green's function calculation in second quantization within a fixed-particle manifold and note that this approach may be valuable for simulation more broadly. Aside from solving linear systems, fast inversion also allows us to develop fast algorithms for computing matrix functions, such as the efficient preparation of Gibbs states. Furthermore, we introduce two efficient approaches for such a task, based on the contour-integral formulation and the inverse transform, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cooperative lane control application for fully connected and automated vehicles at multilane freeways

Advances in communications technology have made the development of connected and automated vehicle (CAV) applications that may potentially replace traditional, gantry operated lane control signals (LCSs) possible. Here, we develop the concept of a prototype CAV-enabled LCS application and provides a preliminary assessment of the potential improvement it offers over traditional LCS. Real-world data obtained from an LCS on I-66 in Northern Virginia was used to calibrate and validate a baseline simulation model. Further, the current lane control scenarios utilized in the Northern Virginia LCS were identified and relevant data resulting from implementation of those scenarios were collected to model the LCS in a simulation environment. The performance of real-world LCS was then compared to a prototype CAV-enabled LCS application developed in this research. The CAV-enabled LCS application consistently outperformed the traditional LCS with increased throughput and speeds. On average, an increase of 18.4%, 9.6% and 12.8% in throughput was observed for three selected scenarios under the best case of a 1 sec headway. Furthermore, the CAV-enabled LCS application was also found to reduce volatility, represented by variation in acceleration and deceleration regimes, by an average of 25.6% and 49.6%. The reduction in turbulence in the traffic stream may indicate potential improved safety with the CAV system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Multi-century dynamics of the climate and carbon cycle under both high and net negative emissions scenarios

Abstract. Future climate projections from Earth system models (ESMs) typically focus on the timescale of this century. We use a set of five ESMs and one Earth system model of intermediate complexity (EMIC) to explore the dynamics of the Earth's climate and carbon cycles under contrasting emissions trajectories beyond this century to the year 2300. The trajectories include a very-high-emissions, unmitigated fossil-fuel-driven scenario, as well as a mitigation scenario that diverges from the first scenario after 2040 and features an “overshoot”, followed by a decrease in atmospheric CO2 concentrations by means of large net negative CO2 emissions. In both scenarios and for all models considered here, the terrestrial system switches from being a net sink to either a neutral state or a net source of carbon, though for different reasons and centered in different geographic regions, depending on both the model and the scenario. The ocean carbon system remains a sink, albeit weakened by carbon cycle feedbacks, in all models under the high-emissions scenario and switches from sink to source in the overshoot scenario. The global mean temperature anomaly is generally proportional to cumulative carbon emissions, with a deviation from proportionality in the overshoot scenario that is governed by the zero emissions commitment. Additionally, 23rd century warming continues after the cessation of carbon emissions in several models in the high-emissions scenario and in one model in the overshoot scenario. While ocean carbon cycle responses qualitatively agree in both globally integrated and zonal mean dynamics in both scenarios, the land models qualitatively disagree in zonal mean dynamics, in the relative roles of vegetation and soil in driving C fluxes, in the response of the sink to CO2, and in the timing of the sink–source transition, particularly in the high-emissions scenario. The lack of agreement among land models on the mechanisms and geographic patterns of carbon cycle feedbacks, alongside the potential for lagged physical climate dynamics to cause warming long after CO2 concentrations have stabilized, points to the possibility of surprises in the climate system beyond the 21st century time horizon, even under relatively mitigated global warming scenarios, which should be taken into consideration when setting global climate policy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Parallel computing for power system climate resiliency: Solving a large-scale stochastic capacity expansion problem with mpi-sppy

Here we propose a nodal stochastic generation and transmission expansion planning model that incorporates the output from high-resolution global climate models through load and generation availability scenarios. We implement our model in Pyomo and perform computational studies on a realistically-sized test case of the California electric grid in a high performance computing environment. We propose model reformulations and algorithm tuning to efficiently solve this large problem using a variant of the Progressive Hedging Algorithm. We utilize the parallelization capabilities and overall versatility of mpi-sppy, exploiting its hub-and-spoke architecture to concurrently obtain inner and outer bounds on an optimal expansion plan. Initial results show that instances with 360 representative days on a system with over 8,000 buses can be solved to within 5% of optimality in under 4 h of wall clock time, a first step towards solving a large-scale power system expansion planning problem across a wide range of climate-informed operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Updating Nuclear Energy Cost Estimates for Net Zero World Initiative

Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Potential impacts of mercury released from thawing permafrost

Abstract Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements

Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.

PMU, noise emulation, synthetic measurements, deep↗
DOE OSTI2021

Evaluation of Tritium Behavior in Forest Vegetation for the Purpose of Determining Appropriate Non-Zero Deposition Velocities for Tritium Oxide

Modeling and field measurements have been conducted between 2019 and 2021 to assess the practicality of using a non-zero deposition velocity for safety basis estimates of tritium oxide fate and transport modeling. A model was developed which used a complex deposition algorithm designed to assess how tritium oxide would mix based on the turbulent motions and wind speed effects that the forest canopy has on the atmosphere. The model was driven based on measurements of wind and turbulence taken from the Aiken AmeriFlux Tower which measures these properties at five levels located within and just above the forest. The model was then validated against a series of field experiments which were designed to test the model predictions and estimate the deposition velocity occurring over the forest environment at the Savannah River Site. The field releases used deuterium oxide as a surrogate for tritium oxide and was released as a fine mist which rapidly evaporated, creating a gaseous tracer in the atmosphere. Using air samplers, the elevations in deuterium concentration in the air relative to background measurements was assessed and then modeled. Generally, the numerical model tended to underpredict the amount of deuterium being mixed from above the canopy to the forest floor, indicating that the predictions it provides are still conservative relative to what was measured during the field experiments. Across a suite of modeling runs, the 95 th and 99 th percentile deposition velocities were estimated to be 1.2 and 0.7 cm s -1 , respectively. Estimated deposition velocities in the 2021 field experiments, which specifically assessed a release above the forest canopy and its mixing to the surface, predicted deposition velocities ranging from 1.75 to 6.61 cm s -1 . While these field releases do not cover all possible meteorological conditions, it seems appropriate to use a non-zero deposition velocity when performing safety-basis modeling of tritium oxide. The recommendation presented in this report is to use 1.0 cm s -1 . This is between the 95 th and 99 th percentile value estimated from the modeling study, suggesting it should be appropriate for the majority of release scenarios given the model’s apparent conservatism relative to field measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Improving Dose Modeling With Dynamic Modeling Tools [Slides]

Utilities aiming for higher fuel enrichment for power uprates or extended operation times before refueling must conduct a new dose analysis. Current conservative dose estimation standards may cause utilities to exceed regulatory limits for proposed increased fuel enrichment. A more accurate modeling of doses from reactor accidents can lower these conservative assumptions. Prescott et al. (2022) demonstrated that the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) software tool, developed at Idaho National Laboratory (INL), can be coupled with the Modular Accident Analysis Program (MAAP5) for dynamic accident analysis in reactor plants. EMRALD forms models of potential accident scenarios, while MAAP5 simulates the accident progression and dose consequences. By integrating these software tools with utility-specific data, a more precise estimation of dose consequences from plant accidents can be achieved. Preliminary findings indicate that EMRALD provides accurate mean core damage frequencies for generalized accident scenarios. Future work includes expanding the model to account for plant-specific data and mitigation factors.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Nuclear winter - Global consequences of multiple nuclear explosions

The results of a computerized simulation of the potential global environmental effects of dust and smoke clouds that would be generated by a nuclear war are presented. Short term effects of blast, fire, and radiation are neglected in the series of physical models that include a nuclear war scenario, a particle microphysics model, and a radiative convective model. Account is taken of the altitude-dependent dust, smoke, radioactivity, and NO(x) injections, the temporal evolution of dust and smoke clouds, land and ocean environments, and temperature contrasts. A nuclear exchange would produce thousands of individual smoke and dust clouds rising up to 30 km altitude in the midlatitudes. The smoke, dust, and radioactive debris would cover the entire midlatitudes within 1-2 weeks. The smoke would arise from conflagrations of forests, suburbs, and urban areas. Obscuration of sunlight would induce subfreezing temperatures for several months, disruption of the global circulation patterns, and the arrival of a nuclear winter, followed and accompanied by radioactive fallout, pyrogenic air pollution, and UV-B flux enhancements. It is estimated that a total of only 100 Mtons would be sufficient to plunge the Northern Hemisphere summer to subfreezing temperatures lasting months. Since the probable exchange in a nuclear war would exceed 5000 Mtons, it is expected that many species, including humans, may not survive the war.

Turco, R. P.↗
NASA NTRS2018

New Formation Models for the Kepler-36 System

Formation of the planets in the Kepler-36 system is modeled by detailed numerical simulations according to the core-nucleated accretion scenario. The standard model is updated to include the dissolution of accreting rocky planetesimals in the gaseous envelope of the planet, leading to substantial enrichment of the envelope mass in heavy elements and a non-uniform composition with depth. For Kepler-36 c, models involving in situ formation and models involving orbital migration are considered. The results are compared with standard formation models. The calculations include the formation (accretion) phase, as well as the subsequent cooling phase, up to the age of Kepler-36 (7 Gyr). During the latter phase, mass loss induced by stellar XUV radiation is included. In all cases, the results fit the measured mass, 7.84 M, and radius, 3.68 R, of Kepler-36 c. Two parameters are varied to obtain these fits: the disk solid surface density at the formation location, and the "efficiency" factor in the XUV mass loss rate. The updated models are hotter and therefore less dense in the silicate portion of the planet and in the overlying layers of H/He, as compared with standard models. The lower densities mean that only about half as much H/He is needed to be accreted to fit the present-day mass and radius constraints. For Kepler-36 b, an updated in situ calculation shows that the entire H/He envelope is lost, early in the cooling phase, in agreement with observation.

planets and satellites:formation↗
NASA NTRSDate not supplied

Radiation Transport Models in Space: from Supernovae to Cells

Humans embarking on deep space exploration missions will encounter persistent exposure to galactic cosmic rays (GCR) - an energetic and highly complex radiation field that is unlike anything found on Earth. Exposure to such radiation fields is attributed to various adverse health effects, including cancer, cardiovascular disease, and cognitive impairment and is identified by NASA as one of the five main hazards of human spaceflight. It is therefore critical to be able to fully characterize the exposure received by humans behind shielding in space and project consequent health risks. A wide variety of computational models have been developed over the years to help meet this requirement. In this talk, an overview of the GCR environment in deep space is provided. Methods of propagating GCR fields through the shielding that protects humans in space are described along with simulation tools used to assess biological damage at the cellular scale. Finally, the NASA cancer risk model is briefly described, and risk projections are provided for various mission scenarios. Radiation transport models and solution methods pervade many aspects of this talk. For example, the GCR spectrum impinging on spacecraft is determined by solving the Fokker-Planck transport equation to propagate cosmic rays (believed to originate from supernovae) from the edge of the heliosphere to the vicinity of Earth. The Boltzmann transport equation is solved to transport this GCR spectrum through shielding and human tissue. Monte Carlo methods are used to simulate the transport of low energy electrons that dominate biological damage at the cellular scale. Progress and challenges in each of these areas will be highlighted.

Tony C. Slaba↗