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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 109 records · Page 6

Application of Extended Messinger Models to Complex Geometries

Since, ice accretion can significantly degrade the performance and the stability of an airborne vehicle, it is imperative to be able to model it accurately. While ice accretion studies have been performed on airplane wings and helicopter blades in abundance, there are few that attempt to model the process on more complex geometries such as fuselages. This paper proposes a methodology that extends an existing in-house Extended Messinger solver to complex geometries by introducing the capability to work with unstructured grids and carry out spatial surface streamwise marching. For the work presented here commercial solvers such as STAR-CCM+ and ANSYS Fluent are used for the flow field and droplet dispersed phase computations. The ice accretion is carried out using an in-house icing solver called GT-ICE. The predictions by GT-ICE are compared to available experimental data, or to predictions by other solvers such as LEWICE and STAR-CCM+. Three different cases with varying levels of complexity are presented. The first case considered is a commercial transport airfoil, followed by a three-dimensional MS(1)-317 swept wing. Finally, ice accretion calculations performed on a Robin fuselage have been discussed. Good agreement with experimental data, where applicable, is observed. Differences between the ice accretion predictions by different solvers have been discussed.

Gupta, Avani↗

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

Modeling and Analysis of Stirling Power Convertors

NASA Glenn’s Thermal Energy Conversion Branch is supporting the development of the next generation free-piston Stirling power convertors for Dynamic Radioisotope Power Systems (DRPS). American Superconductor (AMSC) and Sunpower Inc. are the two of the firms under contract to develop the Flexure Isotope Stirling Convertor (FISC) and the Sunpower Robust Stirling Convertor (SRSC), respectively, to meet DRPS requirements. To comprehend and forecast convertor performance, Sage, ANSYS® Maxwell, and ANSYS® Fluent were used to model the Stirling thermodynamic cycle, alternator electromagnetics, and piston and displacer dynamics.

Stirling↗

Modeling and Analysis of Stirling Power Convertors

NASA Glenn’s Thermal Energy Conversion Branch is supporting the development of the next generation free-piston Stirling power convertors for Dynamic Radioisotope Power Systems (DRPS). American Superconductor (AMSC) and Sunpower Inc. are the two of the firms under contract to develop the Flexure Isotope Stirling Convertor (FISC) and the Sunpower Robust Stirling Convertor (SRSC), respectively, to meet DRPS requirements. To comprehend and forecast convertor performance, Sage, ANSYS® Maxwell, and ANSYS® Fluent were used to model the Stirling thermodynamic cycle, alternator electromagnetics, and piston and displacer dynamics.

Stirling↗

EMU CO2 Washout Comparative Assessments for the HAB/HAP-E in support of EVA 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) model was developed to assess the effect that the absorbent material has on the concentration of carbon dioxide in the EMU helmet. Within a small, closed volume such as a helmet, some amount of the carbon dioxide produced by the suit-wearer will be re-inhaled before being cleared from the oral-nasal region. The ability of the suit to remove carbon dioxide is referred to as CO2 washout. Pathological levels of inhaled CO2 (hypercapnia) are associated with dizziness, fatigue, and headaches. The CFD model was built in ANSYS Fluent and adapted to assess CO2 washout in a variety of scenarios grouped into three categories: purge cases, varying metabolic rates, and varying sorbent material configurations. The presence of the sorbent material did not prove detrimental to CO2 washout in the helmet.

Moses Navarro↗

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Rose Baukus↗

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the Volume of Fluid (VOF) and Sharp Interface multiphase 2D axisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. Turbulence modeling; turbulence damping at the interface; and using constant vs. temperature dependent fluid properties were shown to have the most profound influence on predicted tank pressures and temperatures. Current study indicates that including phase change at the interface into the computational model is crucial for accurate prediction of the tank self-pressurization process. The effect of accommodation coefficient was also studied. Tank pressure values predicted by the VOF, and Sharp Interface models are within 4% of the experimental ones.

Computational Fluid Dynamics↗

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-Phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the VOF and Sharp Interface multiphase 2Daxisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. These parameters include: the effect of turbulence modeling and turbulence damping at the interface; the effect of constant vs. temperature dependent fluid properties; the effect of accommodation coefficient; the effect of modeling phase change at the interface and the effect of the fill level.

Computational Fluid Dynamics↗

EMU CO2 Washout Comparative Assessments for the HAB/HAP-E in Support of EVA 80

After water was reported in the Extravehicular Mobility Unit (EMU) helmet during ISS US EVA 80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) model was developed to assess the effect that the absorbent material has on the concentration of carbon dioxide in the EMU helmet. Within a small, closed volume such as a helmet, some amount of the carbon dioxide produced by the suit-wearer will be re-inhaled before being cleared from the oral-nasal region. The ability of the suit to remove carbon dioxide is referred to as CO2 washout. Pathological levels of inhaled CO2 (hypercapnia) are associated with dizziness, fatigue, and headaches. The CFD model was built in ANSYS Fluent and adapted to assess CO2 washout in a variety of scenarios grouped into three categories: ventilation cases, varying metabolic rates, and varying sorbent material configurations. The presence of the sorbent material did not prove detrimental to CO2 washout in the helmet.

Moses Navarro↗

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Baukus↗

EMU CO2 Washout Comparative Assessments for the HAB/HAP-E in Support of EVA 80

After water was reported in the Extravehicular Mobility Unit (EMU) helmet during ISS US EVA 80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) model was developed to assess the effect that the absorbent material has on the concentration of carbon dioxide in the EMU helmet. Within a small, closed volume such as a helmet, some amount of the carbon dioxide produced by the suit-wearer will be re-inhaled before being cleared from the oral-nasal region. The ability of the suit to remove carbon dioxide is referred to as CO2 washout. Pathological levels of inhaled CO2 (hypercapnia) are associated with dizziness, fatigue, and headaches. The CFD model was built in ANSYS Fluent and adapted to assess CO2 washout in a variety of scenarios grouped into three categories: ventilation cases, varying metabolic rates, and varying sorbent material configurations. The presence of the sorbent material did not prove detrimental to CO2 washout in the helmet.

Moses Navarro↗

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Baukus↗

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗

A Summary of Recent SBIR and STTR Projects in Support of Cryogenic Fluid Management Modeling

Over the last five years, NASA has invested in development of sub-models to improve the current capabilities of Computational Fluid Dynamics (CFD) codes utilized for cryogenic fluid management (CFM) predictions. The goal is for the submodels to be modular so that they can easily be implemented into NASA’s CFD codes such as ANSYS Fluent, Siemens STAR-CCM+, and Streamline Numerics Loci-Stream. These technologies are being developed through Small Business Innovative Research (SBIR) and Small Business Technology Transfer (STTR) contracts under the CFM subtopic solicitation and funded by the CFM Portfolio Project. All contracts presented include cryogenic experiments to enable model validation. A sub-grid boiling model has been developed by Combustion Research and Flow Technology Inc. and Massachusetts Institute of Technology for cryogenic line chilldown predictions and has completed Phase III. A spray chill-and-fill model for cryogenic tankage is being developed by Combustion Research and Flow Technology Inc. and University of Connecticut and is currently in Phase II. Last, film condensation modeling to support cryogenic liquefaction was progressed through a Phase I contract with Combustion Research and Flow Technology Inc. and University of Connecticut. A summary of accomplishments for each contract is presented.

cryogenics↗

Computational Fluid Dynamics Simulation of Methane Slosh and Drain Experiments

NASA possesses a wealth of historical cryogenic experiments that provide valuable insights into the design, troubleshooting, and understanding involved in the complex fluid and thermodynamics of managing cryogenic propellants. One approach to leveraging these historical datasets is by simulating these experiments to validate the accuracy of simulation environments and constituent models. This study focused on simulating a selection of the K site test series for both static and sloshing pressurized liquid methane draining experiments conducted at NASA in the 1970’s, utilizing computational fluid dynamics. The simulations were performed in the ANSYS FLUENT environment using the Volume of Fluid (VOF) numerical approach. A k-omega turbulence model was used with interfacial turbulence damping, and accurately predicted the amount of pressurant needed to maintain the required tank pressure throughout the static drain. The static simulation predicted the temperature stratification in the ullage observed at the end of the drain. During the methane expulsion with sloshing test, many features were successfully captured using the k-omega turbulence model with interfacial turbulence damping included. The rate of phase change and liquid temperature was overpredicted compared to the experimental measurements. The overprediction may be attributed to uncertainties in the vessel geometry, methane pressurant temperature and composition, and methodological differences in how the sloshing frequency was adjusted during the expulsion.

Cryogenic Propellants↗

Physics-Based Modeling and Simulation of Self-Reacting Friction Stir Welding Using Computational Fluid Dynamics

A physics-based model was developed to simulate the behavior of material in a self-reacting friction stir welding (SR-FSW) process for the joining of metals. This steady-state model builds upon fundamental computational fluid dynamic (CFD) principles within Ansys Fluent to solve the discretized equations. The effective viscosity is calculated using a viscoplastic model using a Sheppard-Wright formulation of flow stress. Numerous advancements have been made in the incorporated physics including (1) temperature-dependent material properties; (2) locally adaptable flow and thermal boundary conditions; and (3) adapting material properties in nugget in response to microstructural changes. Simulation strategies to accelerate computation and improve numerical stability include adapting the mesh refinement and solver relaxation factors during simulation. The result is a highly robust and computationally efficient model capable of providing the material flow and temperature history across the domain. As material history determines the local microstructure and ultimately weld strength, an accurate and detailed physics-based model has the potential to accelerate SR-FSW process development. The model is highly adaptable to changes in process parameters, tool design, or alloy.

Process Modeling↗

Photophoretic Propulsion Enabling Mesosphere Exploration NIAC Phase I Final Report

This Phase I report presents a comprehensive study on photophoretic flyers—innovative, ultralight, solar-powered vehicles that harness photophoretic forces generated via Knudsen pumping to achieve sustained flight in the mesosphere (50–80 km altitude). By integrating advanced materials such as nanocardboard— characterized by its extremely low areal density (~1 g/m²) and high bending stiffness—with ultrathin light-absorbing coatings, the project converts incident solar radiation directly into a directed thrust. Extensive experimental investigations, coupled with high-fidelity computational fluid dynamics (CFD) simulations using ANSYS Fluent, validate the concept across various three-dimensional geometries, including spherical, conical, and rocket-shaped configurations. These simulations bridge the gap between free-molecular and continuum flow regimes, demonstrating that optimized designs can generate lift forces sufficient to support kilogram-scale payloads even in low-pressure environments. At the heart of this innovation is the use of Knudsen pumping, where temperature gradients across porous surfaces induce directional gas flow, creating a modest overpressure that provides lift. The report introduces an analytical framework that interpolates between the well-known low-Reynolds number drag regime and the high-Reynolds number momentum theory. This model accurately predicts lift based on design parameters such as microchannel dimensions, porous wall geometry, areal density, and nozzle exit area. For instance, simulations indicate that 10-meter-scale structures with carefully engineered porous walls can achieve the necessary pressure differential to support scientifically significant payloads (~1 kg). The study also explores a hybrid propulsion approach that combines solar buoyancy with photophoretic lift. Initially, solar heating creates a buoyant force that elevates the flyer to mesospheric altitudes. Once in the optimal pressure range, the photophoretic mechanism—powered by Knudsen pumping—takes over as the primary source of lift, ensuring stable, long-duration flight. This dual-mode operation not only facilitates the deployment of photophoretic flyers but also broadens the potential applications for mesospheric exploration. In addition to propulsion, the report investigates the integration of photophoretic thrusters for trajectory control of existing research balloons in the upper stratosphere. By dynamically adjusting the nozzle orientation and controlling the flow-through velocity, these thrusters provide precise maneuverability, enabling the flyers to counteract atmospheric disturbances and adjust their flight paths in real time. For example, a photophoretic thruster approximately 7.5 by 7.5 meters in size could be unfolded below a payload gondola of a 60 million-cubic-foot zero-pressure balloon. Such a thruster can provide horizontal speed control of approximately 1 m/s using only sunlight and no moving parts (except those needed to track the Sun and control the jet direction). Importantly, photophoretic thrusters operate more efficiently at higher altitudes, which is complementary to known trajectory control techniques, such as propellers and tethered wings, which are more effective at lower altitudes. Finally, the report identifies three scientific research thrusts where mesospheric aircraft technology can have a profound impact: atmospheric tides, characterization of gravity waves, and investigation of mesospheric instabilities. Overall, the findings of this Phase I project represent a significant advancement in photophoretic propulsion technology. By demonstrating that large-scale, ultralight structures can be powered solely by solar radiation—via carefully engineered Knudsen pumping—this work lays a robust foundation for scalable, near-space flight architectures. Future refinements in material fabrication, structural optimization, and integrated trajectory control are expected to further enhance performance, paving the way for operational demonstrations that could revolutionize atmospheric science, remote sensing, and communication networks.

Knudsen Pump↗