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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗
NASA NTRS2016

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Gastellu-Etchegorry, Jean-Philippe↗
DOE OSTI2025

The impact of simplified window and exhaust fan assumptions on indoor air quality in multifamily buildings

In residential buildings, the indoor air quality can be significantly affected by ventilation measures initiated by occupants, including the operation of windows and in-unit exhaust fans in kitchens and bathrooms. Many simulations simplify these factors by disregarding window opening behaviors and using fixed schedules for exhaust fan operation across all residential units. To estimate the impact of these simplifications in the U.S. context, this study used coupled CONTAM and EnergyPlus models to simulate airflow and contaminant transport in multifamily buildings. The coupled models parametrically varied climate zone, building airtightness, and mechanical ventilation system types. The study conducted a sensitivity analysis on two key occupant behaviors: (1) operating kitchen and bathroom exhausts on different schedules in individual dwelling units, and (2) scheduling open windows on ground and top floors. The simplified assumptions (i.e. uniform in-unit exhaust fan operation and window operation) had a minimal impact on inter-unit air flow and contaminant transport simulations across a broad range of building air leakage and mechanical ventilation system types. These findings suggest that for buildings with tight construction it is reasonable for most modelling and simulation efforts to ignore the effects of non-uniform exhaust fan operation and window opening.

Occupant behavior↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2025

Caustic Neutralization and Precipitation of Acidic Dissolved Simulated Stainless Steel–Clad Plutonium and Plutonium/Uranium Nuclear Fuel

Simulated dissolved stainless steel (SS) clad Pu and Pu/U nuclear fuel in HNO 3 was neutralized to a free hydroxide (OH - ) concentration of 0.6 M. A thermal neutron poison, Gd, was added to the simulants at concentrations of either ~3 - 6 g/L or ~37 - 38 g/L. The supernate Pu concentration the day of neutralization ranged from 0.48 to 8.75 mg/L. The supernate Pu concentration of a simplified simulant neutralized to 0.6 M OH - above precipitated solids containing Pu was demonstrated to decrease over 18 days. A significant portion of precipitated Pu was found to be insoluble in 8 M HNO 3 at ambient temperature, but essentially quantitative Pu dissolution was achieved in 11.5 M HNO 3 /0.1 M KF at 100 °C. The difficulty in dissolving the Pu precipitate is believed to be due to the formation of refractory PuO 2 •xH 2 O during the neutralization process. Initial Gd concentrations of ~37 – 38 g/L were found to result in a greater Al precipitation when neutralized to 0.6 M OH - than initial Gd concentrations of ~3 – 6 g/L. Physical properties of the resultant slurries were measured and used to calculate limiting flowrates and slurry velocities by gravity only in transfer piping between the Savannah River Site’s H-Canyon Facility and the Concentration, Storage, and Transfer Facility (CSTF). These results were compared to calculated deposition velocities to predict if solids would settle during the transfer. The Newtonian model was found to be reasonable for each diluted slurry evaluated. Deposition velocities of Pu containing slurries are lower than nuclear fuel slurries primarily composed of U due to the high density of Pu solids. In conclusion, dilution of slurries reduces the margin between the slurry and deposition velocities due to the reduction in viscosity because higher viscous forces on the particles promote maintained suspension.

Actinide Neutralization↗
NASA NTRSDate not supplied

Deep Space Radiation Affects Neurovascular Functions in Human Organ-on-a-Chip Models

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high- linear energy transfer (LET) particles such as 56 Fe ions, cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates the interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal health and neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue/organ analogs. Therefore, we utilized a high-throughput human 3D organ-on-a-chip system, seeded with induced pluripotent stem cell-derived endothelial cells, astrocytes and neurons, to study human neurovascular responses to simulated deep space radiation. We investigated BBB permeability, oxidative stress, cellular and tissue damage, and secreted factors over the time period of 24 hours-1 week after irradiation with 0.25-0.5 Gy 5-ion simplified simulated galactic cosmic rays and 0.3-0.8 Gy high-LET 600MeV/n 56 Fe particles, and compared the outcomes to low-LET irradiation with 0.1-1 Gy doses of X-rays and gamma rays. Both high and low-LET radiation increased neurovascular permeability, caused oxidative stress, damaged endothelial cells and tight junctions, and altered expression of inflammatory cytokines. Ionizing radiation- induced neurovascular permeability and oxidative stress peaked at 3 days after irradiation and were further exacerbated by the presence of astrocytes. Furthermore, in response to particle irradiation, astrocytes stimulated interleukin-1 signaling by inhibiting the expression of interleukin-1 receptor antagonist. Thus, we also evaluated interleukin-1 receptor antagonist as a potential countermeasure against particle radiation. Ultimately, our results may help develop countermeasures to mitigate human CNS damage in deep space exploration.

Sonali D Verma↗
NASA NTRSDate not supplied

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗
NASA NTRS2000

Analytic Guided-Search Model of Human Performance Accuracy in Target- Localization Search Tasks

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

Eckstein, Miguel P.↗
DOE OSTI2023

Thermal Hydraulic Modeling of an Advanced Nuclear Reactor using open-source MOOSE tools

The aim of this study is to develop model of a small High Temperature Gas cooled Reactor (HTGR) including the balance of plant. This microreactor produces electricity using the thermal power of the nuclear reaction. This work utilizes the MOOSE Multiphysics simulation tools, which are mainly developed at Idaho National Laboratory (INL, Idaho, United States of America). Its thermal-hydraulics and Heat conduction Modules are used to study the fluids behavior in the primary loop and power conversion system and their interactions with the heating structures. More specifically, one verifies that the temperatures, pressures and mass flow rates of the fluids in both loops are consistent and that, at the same time, all the power transfers occur as expected. Moreover, the various mechanical components characteristics (turbine, compressor, pump) are adapted to the reactor operating conditions. This first analysis is conducted using simplified and one-dimensional model for the core. Ultimately, the obtained results are used to build a higher fidelity core model. This step aims to verify that the initial simplified simulation is consistent with the three-dimensional core modeling. In addition, the calculated material temperatures are checked. This study provides a fairly complete model of the thermal hydraulic phenomena for a particular design of High Temperature Gas cooled Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1991

Simulation and analyses of the aeroassist flight experiment attitude update method

A method which will be used to update the alignment of the Aeroassist Flight Experiment's Inertial Measuring Unit is simulated and analyzed. This method, the Star Line Maneuver, uses measurements from the Space Shuttle Orbiter star trackers along with an extended Kalman filter to estimate a correction to the attitude quaternion maintained by an Inertial Measuring Unit in the Orbiter's payload bay. This quaternion is corrupted by on-orbit bending of the Orbiter payload bay with respect to the Orbiter navigation base, which is incorporated into the payload quaternion when it is initialized via a direct transfer of the Orbiter attitude state. The method of updating this quaternion is examined through verification of baseline cases and Monte Carlo analysis using a simplified simulation, The simulation uses nominal state dynamics and measurement models from the Kalman filter as its real world models, and is programmed on Microvax minicomputer using Matlab, and interactive matrix analysis tool. Results are presented which confirm and augment previous performance studies, thereby enhancing confidence in the Star Line Maneuver design methodology.

Carpenter, J. R.↗
NASA NTRS2018

Numerical Simulation of a Simplified High-Lift CRM Configuration Embedded with Fluidic Actuators

Numerical simulations have been performed for a simplified high-lift configuration that is representative of a modern transport airplane. This configuration includes a leading-edge slat, fuselage, wing, nacelle-pylon and a simple hinged flap. The suction surface of the flap is embedded with multiple rows of fluidic actuators to reduce the extent of reversed flow regions and improve the aerodynamic performance of the configuration with flap in a deployed state. In the current paper, a Lattice Boltzmann Method based high-fidelity computational fluid dynamics (CFD) code, known as PowerFLOW® is used to simulate the entire flow field associated with this configuration, including the flow inside the actuators. A fully compressible version of the PowerFLOW® code that has been validated for high speed flows is used for the present simulations to accurately represent the transonic flow regimes that are encountered in the flow field generated by the actuators operating at higher mass flow (momentum) rates required to mitigate reverse flow regions on the suction surfaces of the main wing and the flap. The numerical solutions predict the expected trends in aerodynamic forces as the actuation levels are increased. More efficient active flow control (AFC) systems and actuator arrangement for lift augmentation are emerging based on the parametric studies conducted here prior to wind tunnel tests. These numerical solutions will be compared with experimental data, once such data becomes available.

Vatsa, Veer N.↗
DOE OSTI2025

How Topological Polymer Loops on the Nanoparticle Surface Control the Mechanical Properties of Nanocomposites

Carbon black (CB) and silica (SiO 2 ) filled elastomers are known to be the most successful polymer nanocomposites (PNCs) in industry, where “bound rubber (BR)” (i.e., polymer chains that are physically or chemically adsorbed on the nanofiller surface) plays a critical role in their reinforcement. Here, we report a molecular-scale mechanism underlying the “BR-induced reinforcement” by integrating neutron scattering experiments and molecular dynamics simulations. Simplified non-cross-linked SiO 2 -filled polybutadiene (PB) and CB-filled PB reveal the critical role of topological polymer loops in the BR for the enhanced mechanical performance. The average loop size on the SiO 2 surface modified with a silane coupling agent is much smaller than that on the CB surface and the loops on the SiO 2 surface are densely formed, preventing interdigitation with the matrix chains. On the other hand, the larger, uncrowded loops formed on the CB surface facilitate the interdigitation with the matrix polymer chains even near the filler surface. In this way, a strong connectivity is established between a matrix and a nanofiller, resulting in an adhesive filler–polymer interface. Furthermore, our findings shed light on rich and complex physics and materials design problems in PNCs, where the topological polymer structure on the nanofiller surface directly controls the macroscopic mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluation of the Energy, Hygrothermal, and Thermal Capacity Performance of Cross-Laminated Timber

Cross-laminated timber (CLT) construction is gaining momentum in the US because it offers multiple advantages over traditional construction methods. Benefits that have received the most attention focus on constructability, the environment, and protection (e.g., blast resistance), although CLT construction is likely to offer other benefits, as well. Still, these have not been studied at length because such evaluations are costly, requiring long-term assessments in an actual building and specialized technical knowledge. Among the possible benefits, CLT construction likely provides a higher-performing building envelope. Using CLT panels to enclose a building means fewer joints in the opaque envelope than what is required in traditional stick-framed construction. Fewer joints mean fewer locations where the air- and water-resistive barrier (WRB) could be compromised; thus, a CLT building enclosure may require less maintenance and have a longer lifespan than a traditionally built structure because of fewer air and water leaks. In addition, CLT’s thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours, reducing operational energy consumption throughout the lifetime of the CLT building (Salonvaara et al., 2022). Furthermore, more stable indoor temperatures can increase occupant comfort. The CLT’s thermal mass can also reduce energy costs by adjusting to utility time-of-use pricing without affecting occupant comfort. The ability of CLT buildings to bridge periods without HVAC operation prepares them for future grid interaction and provides a certain level of resilience against power outages. Researchers have attempted to quantify these benefits; however, their work is based on simplified simulations with numerous assumptions. To correctly understand the benefits, an actual building must be monitored. Therefore, information needs to be gathered on indoor and outdoor temperatures, HVAC energy consumption, thermostat setpoints, temperatures, and thermal transport in CLT components to comprehend how these parameters are affected by the CLT’s thermal mass. These data are needed to reduce the number of assumptions and calibrate simulation models to optimize HVAC controls to minimize overall energy consumption, reduce energy use and higher fees during peak demand, and maintain occupant comfort. Additionally, the calibrated simulation model allows the optimization exercise to be repeated in various US climates. Potential benefits can be tailored to buildings in various locations, and decisions can be made on where CLT construction could be most advantageous. Furthermore, monitoring and simulation results are needed to evaluate the durability of the CLT structures in different climates. This project’s researchers gathered information to help understand and quantify the benefits of CLT buildings concerning operational energy, moderated indoor temperatures, and comfort; the dynamic operation to provide grid services; and resilience in times of power outage. Through the corroboration of simulation models with real-world measurements, this study paves the way for extrapolating findings to other climatic zones and building typologies, thereby broadening the understanding of CLT’s multifaceted benefits and reinforcing its position as a material of choice in sustainable construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integrated Off-gas System: A Preconceptual Design of an Integrated Off-Gas Treatment System

The U.S. has a vested interest in the advancement of nuclear energy to achieve aggressive net-zero goals, with reprocessing and recycling of used nuclear fuels (UNF) playing a vital role. It will not be possible to meet U.S. regulatory requirements without robust off-gas treatment, so it is crucial to advance treatment technologies to facilitate the design of future reprocessing facilities. For many years, teams of researchers across the U.S. Department of Energy (DOE) National Laboratory complex have been investigating off-gas treatment technologies for the capture and removal of volatile radionuclides (i.e., 85 Kr, Xe, 14 C, and 129 I) and oxides of nitrogen (NO X ) that are produced from reprocessing. These investigations have been focused on developing individual technologies for the capture of Kr, Xe, iodine, and CO 2 . Capture technologies for each constituent were tested independently from one another by utilizing nonradioactive surrogates to simulate simplified off-gas streams. The tests have been relatively small, laboratory-scale experiments of up to approximately 1 L/minute total gas flow rate. To increase the readiness of these technologies for deployment, an integrated test system with a larger-scale capacity is needed to bridge the gap between promising bench scale and fully scalable UNF reprocessing off-gas treatment. This document contains the goals, design basis, functional requirements, preconceptual design, and cost estimates for an integrated off-gas demonstration system for the capture and removal of NO x , Kr, Xe, CO 2 , and iodine at 10× higher throughput than earlier laboratory studies. The order-of-magnitude cost estimate for this system is approximately $\$$886,000. Next phases include conceptual design, detailed design, fabrication, and commissioning.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗
NASA NTRS1975

Design of a video system providing optimal visual information for controlling payload and experiment operations with television

A program was conducted which included the design of a set of simplified simulation tasks, design of apparatus and breadboard TV equipment for task performance, and the implementation of a number of simulation tests. Performance measurements were made under controlled conditions and the results analyzed to permit evaluation of the relative merits (effectivity) of various TV systems. Burden factors were subsequently generated for each TV system to permit tradeoff evaluation of system characteristics against performance. For the general remote operation mission, the 2-view system is recommended. This system is characterized and the corresponding equipment specifications were generated.

Source record↗
NASA NTRS1979

Computed voltage distribution around Solar Electric Propulsion spacecraft

The paper uses the NASCAP computer code to compute voltage distributions around a Solar Electric Propulsion (SEP) spacecraft as it encounters an idealized geomagnetic substorm environment. Consideration is given to both a standard operating voltage and direct-drive voltage configuration. The computations are presented without thruster operations as well as with a simplified, simulated thruster-on representation for direct-drive configuration only. Finally, it is stressed that the computations seeking possible areas of concern in the spacecraft design are exploratory.

Stevens, N. J.↗