Results for “optimization, inverse problems” — Page 8

NASA NTRS2004

Applications of Response Surface-Based Methods to Noise Analysis in the Conceptual Design of Revolutionary Aircraft

Due to the growing problem of noise in today's air transportation system, there have arisen needs to incorporate noise considerations in the conceptual design of revolutionary aircraft. Through the use of response surfaces, complex noise models may be converted into polynomial equations for rapid and simplified evaluation. This conversion allows many of the commonly used response surface-based trade space exploration methods to be applied to noise analysis. This methodology is demonstrated using a noise model of a notional 300 passenger Blended-Wing-Body (BWB) transport. Response surfaces are created relating source noise levels of the BWB vehicle to its corresponding FAR-36 certification noise levels and the resulting trade space is explored. Methods demonstrated include: single point analysis, parametric study, an optimization technique for inverse analysis, sensitivity studies, and probabilistic analysis. Extended applications of response surface-based methods in noise analysis are also discussed.

Hill, Geoffrey A.↗

NASA NTRS1997

Combined Numerical/Analytical Perturbation Solutions of the Navier-Stokes Equations for Aerodynamic (Ejector Nozzle) Flows

In spite of the rapid advances in both scalar and parallel computational tools, the large number and breadth of variables involved in aerodynamic systems make the use of parabolized or even boundary layer fluid flow models impractical for both preliminary design and inverse design problems. Given this restriction, we have concluded that reduced or approximate models are an important family of tools for design purposes. This study of a combined perturbation/numerical modeling methodology with an application to ejector-mixer nozzles (shown schematically in the following figure) is nearing completion. The work is being funded by a grant from the NASA Lewis Research Center to Texas A&M University. These ejector-mixer nozzle models are designed to be of use to the High Speed Civil Transport Program and may be adopted by both NASA and industry. A computer code incorporating the ejector-mixer models is under development. This code, the Differential Reduced Ejector/Mixer Analysis (DREA), can be run fast enough to be used as a subroutine or to be called by a design optimization routine. Simplified conservation equations--x-momentum, energy, and mass conservation--are used to define the model. Unlike other preliminary design models, DREA requires minimal empirical input and includes vortical mixing and a fully compressible formulation among other features. DREA is being validated by comparing it with results obtained from open literature and proprietary industry data. Preliminary results for a subsonic ejector and a supersonic ejector are shown. In addition, dedicated experiments have been performed at Texas A&M. These experiments use a hydraulic/gas flow analog to provide information about the inviscid mixing interface structure. Final validation and documentation of this work is expected by May of 1997. However, preliminary versions of DREA can be expected in early 1997. In summary, DREA provides a sufficiently detailed and realistic ejector-mixer nozzle model at a computational cost compatible with preliminary design applications.

DeChant, Lawrence J.↗

NASA NTRS1976

Elliptic integral solutions to a class of space flight optimization problems

This paper is initially concerned with the minimum-time, exoatmospheric flight of a rocket with constant thrust acceleration magnitude, as in the cases of nuclear and solar electric propulsion. Gravitational acceleration is assumed to be a constant scalar multiple of the radius vector, plus a correction term which is a given function of time. The solution to the state equations is obtained in terms of elliptic integrals. A method is presented for the solution of the two-point boundary-condition problem associated with orbital transfer. At most, the latter method requires iteration upon final time, angle of injection, and two other parameters which are bounded. An example problem is provided which involves a rocket with very low thrust and a spiraling trajectory of many revolutions, but an altitude change of only several hundred miles above the earth. Finally, the original elliptic integral solution is extended to a larger class of low and intermediate thrust problems with constant thrust magnitude, mass decreasing with time, and an inverse square gravitational force.

Andrus, J. F.↗

NASA NTRS1993

A numerical treatment of geodynamic viscous flow problems involving the advection of material interfaces

Effective numerical treatment of multicomponent viscous flow problems involving the advection of sharp interfaces between materials of differing physical properties requires correction techniques to prevent spurious diffusion and dispersion. We develop a particular algorithm, based on modern shock-capture techniques, employing a two-step nonlinear method. The first step involves the global application of a high-order upwind scheme to a hyperbolic advection equation used to model the distribution of distinct material components in a flow field. The second step is corrective and involves the application of a global filter designed to remove dispersion errors that result from the advection of discontinuities (e.g., material interfaces) by high-order, minimally dissipative schemes. The filter introduces no additional diffusion error. Nonuniform viscosity across a material interface is allowed for by the implementation of a compositionally weighted-inverse interface viscosity scheme. The combined method approaches the optimal accuracy of modern shock-capture techniques with a minimal increase in computational time and memory. A key advantage of this method is its simplicity to incorporate into preexisting codes be they finite difference, element, or volume of two or three dimensions.

Lenardic, A.↗

NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗

NASA NTRS1994

Dynamically consistent hydrography and absolute velocity in the eastern North Atlantic Ocean

The problem of mapping a dynamically consistent hydrographic field and associated absolute geostrophic flow in the eastern North Atlantic between 24 deg and 36 deg N is related directly to the solution of the so-called thermocline equations. A nonlinear optimization problem involving Needler's P equation is solved to find the hydrography and resulting flow that minimizes the vertical mixing above about 1500 m in the ocean and is simultaneously consistent with the observations. A sharp minimum (at least in some dimensions) is found, apparently corresponding to a solution nearly conserving potential vorticity and with vertical eddy coefficient less than about 10(exp -5) sq m/s. Estimates of `residual' quantities such as eddy coefficients are extremely sensitive to slight modifications to the observed fields. Boundary conditions, vertical velocities, etc., are a product of the optimization and produce estimates differing quantitatively from prior ones relying directly upon observed hydrography. The results are generally insensitive to particular elements of the solution methodology, but many questions remain concerning the extent to which different synoptic sections can be asserted to represent the same ocean. The method can be regarded as a practical generalization of the beta spiral and geostrophic balance inverses for the estimate of absolute geostrophic flows. Numerous improvements to the methodology used in this preliminary attempt are possible.

Wunsch, Carl↗

NASA NTRS2010

Fast Solution in Sparse LDA for Binary Classification

An algorithm that performs sparse linear discriminant analysis (Sparse-LDA) finds near-optimal solutions in far less time than the prior art when specialized to binary classification (of 2 classes). Sparse-LDA is a type of feature- or variable- selection problem with numerous applications in statistics, machine learning, computer vision, computational finance, operations research, and bio-informatics. Because of its combinatorial nature, feature- or variable-selection problems are NP-hard or computationally intractable in cases involving more than 30 variables or features. Therefore, one typically seeks approximate solutions by means of greedy search algorithms. The prior Sparse-LDA algorithm was a greedy algorithm that considered the best variable or feature to add/ delete to/ from its subsets in order to maximally discriminate between multiple classes of data. The present algorithm is designed for the special but prevalent case of 2-class or binary classification (e.g. 1 vs. 0, functioning vs. malfunctioning, or change versus no change). The present algorithm provides near-optimal solutions on large real-world datasets having hundreds or even thousands of variables or features (e.g. selecting the fewest wavelength bands in a hyperspectral sensor to do terrain classification) and does so in typical computation times of minutes as compared to days or weeks as taken by the prior art. Sparse LDA requires solving generalized eigenvalue problems for a large number of variable subsets (represented by the submatrices of the input within-class and between-class covariance matrices). In the general (fullrank) case, the amount of computation scales at least cubically with the number of variables and thus the size of the problems that can be solved is limited accordingly. However, in binary classification, the principal eigenvalues can be found using a special analytic formula, without resorting to costly iterative techniques. The present algorithm exploits this analytic form along with the inherent sequential nature of greedy search itself. Together this enables the use of highly-efficient partitioned-matrix-inverse techniques that result in large speedups of computation in both the forward-selection and backward-elimination stages of greedy algorithms in general.

Moghaddam, Baback↗

NASA NTRS1991

On designing for quality

The problem of ensuring the required quality of products and/or technological processes often becomes more difficult due to the fact that there is not general theory of determining the optimal sets of value of the primary factors, i.e., of the output parameters of the parts and units comprising an object and ensuring the correspondence of the object's parameters to the quality requirements. This is the main reason for the amount of time taken to finish complex vital article. To create this theory, one has to overcome a number of difficulties and to solve the following tasks: the creation of reliable and stable mathematical models showing the influence of the primary factors on the output parameters; finding a new technique of assigning tolerances for primary factors with regard to economical, technological, and other criteria, the technique being based on the solution of the main problem; well reasoned assignment of nominal values for primary factors which serve as the basis for creating tolerances. Each of the above listed tasks is of independent importance. An attempt is made to give solutions for this problem. The above problem dealing with quality ensuring an mathematically formalized aspect is called the multiple inverse problem.

Vajingortin, L. D.↗

NASA NTRS1991

A unified viscous theory of lift and drag of 2-D thin airfoils and 3-D thin wings

A unified viscous theory of 2-D thin airfoils and 3-D thin wings is developed with numerical examples. The viscous theory of the load distribution is unique and tends to the classical inviscid result with Kutta condition in the high Reynolds number limit. A new theory of 2-D section induced drag is introduced with specific applications to three cases of interest: (1) constant angle of attack; (2) parabolic camber; and (3) a flapped airfoil. The first case is also extended to a profiled leading edge foil. The well-known drag due to absence of leading edge suction is derived from the viscous theory. It is independent of Reynolds number for zero thickness and varies inversely with the square root of the Reynolds number based on the leading edge radius for profiled sections. The role of turbulence in the section induced drag problem is discussed. A theory of minimum section induced drag is derived and applied. For low Reynolds number the minimum drag load tends to the constant angle of attack solution and for high Reynolds number to an approximation of the parabolic camber solution. The parabolic camber section induced drag is about 4 percent greater than the ideal minimum at high Reynolds number. Two new concepts, the viscous induced drag angle and the viscous induced separation potential are introduced. The separation potential is calculated for three 2-D cases and for a 3-D rectangular wing. The potential is calculated with input from a standard doublet lattice wing code without recourse to any boundary layer calculations. Separation is indicated in regions where it is observed experimentally. The classical induced drag is recovered in the 3-D high Reynolds number limit with an additional contribution that is Reynold number dependent. The 3-D viscous theory of minimum induced drag yields an equation for the optimal spanwise and chordwise load distribution. The design of optimal wing tip planforms and camber distributions is possible with the viscous 3-D wing theory.

Yates, John E.↗

NASA NTRS2003

Aerodynamic Design Using Neural Networks

The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.

Rai, Man Mohan↗

NASA NTRS1998

Combined Numerical/Analytical Perturbation Solutions of the Navier-Stokes Equations for Aerodynamic Ejector/Mixer Nozzle Flows

In spite of rapid advances in both scalar and parallel computational tools, the large number of variables involved in both design and inverse problems make the use of sophisticated fluid flow models impractical, With this restriction, it is concluded that an important family of methods for mathematical/computational development are reduced or approximate fluid flow models. In this study a combined perturbation/numerical modeling methodology is developed which provides a rigorously derived family of solutions. The mathematical model is computationally more efficient than classical boundary layer but provides important two-dimensional information not available using quasi-1-d approaches. An additional strength of the current methodology is its ability to locally predict static pressure fields in a manner analogous to more sophisticated parabolized Navier Stokes (PNS) formulations. To resolve singular behavior, the model utilizes classical analytical solution techniques. Hence, analytical methods have been combined with efficient numerical methods to yield an efficient hybrid fluid flow model. In particular, the main objective of this research has been to develop a system of analytical and numerical ejector/mixer nozzle models, which require minimal empirical input. A computer code, DREA Differential Reduced Ejector/mixer Analysis has been developed with the ability to run sufficiently fast so that it may be used either as a subroutine or called by an design optimization routine. Models are of direct use to the High Speed Civil Transport Program (a joint government/industry project seeking to develop an economically.viable U.S. commercial supersonic transport vehicle) and are currently being adopted by both NASA and industry. Experimental validation of these models is provided by comparison to results obtained from open literature and Limited Exclusive Right Distribution (LERD) sources, as well as dedicated experiments performed at Texas A&M. These experiments have been performed using a hydraulic/gas flow analog. Results of comparisons of DREA computations with experimental data, which include entrainment, thrust, and local profile information, are overall good. Computational time studies indicate that DREA provides considerably more information at a lower computational cost than contemporary ejector nozzle design models. Finally. physical limitations of the method, deviations from experimental data, potential improvements and alternative formulations are described. This report represents closure to the NASA Graduate Researchers Program. Versions of the DREA code and a user's guide may be obtained from the NASA Lewis Research Center.

DeChant, Lawrence Justin↗

NASA NTRS2008

NASA Tech Briefs, June 2008

Topics covered include: Charge-Control Unit for Testing Lithium-Ion Cells; Measuring Positions of Objects Using Two or More Cameras; Lidar System for Airborne Measurement of Clouds and Aerosols; Radiation-Insensitive Inverse Majority Gates; Reduced-Order Kalman Filtering for Processing Relative Measurements; Spaceborne Processor Array; Instrumentation System Diagnoses a Thermocouple; Chromatic Modulator for a High-Resolution CCD or APS; Commercial Product Activation Using RFID; Cup Cylindrical Waveguide Antenna; Aerobraking Maneuver (ABM) Report Generator; ABM Drag_Pass Report Generator; Transformation of OODT CAS to Perform Larger Tasks; Visualization Component of Vehicle Health Decision Support System; Mars Reconnaissance Orbiter Uplink Analysis Tool; Problem Reporting System; G-Guidance Interface Design for Small Body Mission Simulation; DSN Scheduling Engine; Replacement Sequence of Events Generator; Force-Control Algorithm for Surface Sampling; Tool for Merging Proposals Into DSN Schedules; Micromachined Slits for Imaging Spectrometers; Fabricating Nanodots Using Lift-Off of a Nanopore Template; Making Complex Electrically Conductive Patterns on Cloth; Special Polymer/Carbon Composite Films for Detecting SO2; Nickel-Based Superalloy Resists Embrittlement by Hydrogen; Chemical Passivation of Li+-Conducting Solid Electrolytes; Organic/Inorganic Polymeric Composites for Heat-Transfer Reduction; Composite Cathodes for Dual-Rate Li-Ion Batteries; Improved Descent-Rate Limiting Mechanism; Alignment-Insensitive Lower-Cost Telescope Architecture; Micro-Resistojet for Small Satellites; Using Piezoelectric Devices to Transmit Power through Walls; Miniature Latching Valve; Apparatus for Sampling Surface Contamination; Novel Species of Non-Spore-Forming Bacteria; Chamber for Aerosol Deposition of Bioparticles; Hyperspectral Sun Photometer for Atmospheric Characterization and Vicarious Calibrations; Dynamic Stability and Gravitational Balancing of Multiple Extended Bodies; Simulation of Stochastic Processes by Coupled ODE-PDE; Cluster Inter-Spacecraft Communications; Genetic Algorithm Optimizes Q-LAW Control Parameters; Low-Impact Mating System for Docking Spacecraft; Non-Destructive Evaluation of Materials via Ultraviolet Spectroscopy; Gold-on-Polymer-Based Sensing Films for Detection of Organic and Inorganic Analytes in the Air; and Quantum-Inspired Maximizer.

Source record↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRSDate not supplied

Recent Developments of Thermal Protection Materials to Enable Lower Cost Space Missions

Introduction: Starting with the Commercial Crew Program, a new paradigm has emerged at NASA. Rather than designing rockets and spacecrafts for every mission optimized to achieve science, NASA has begun to use a service-based model and utilizing public-private partnership in developing the vehicles that can bring broader benefits as well as lower the cost for NASA missions. Commercial companies own and operate those vehicles. This allows NASA to not design missions from the bottom up, and has cost, risk, and schedule savings implications. On the other side, the constraints require meeting the requirements in terms of mass, volume, power, etc. By leveraging NASA developed technologies, commercial companies can quickly demonstrate the commercial mission concept, and, through technology transfer, adopt needed technology to address supply chain problems. A downside is that the technology has to be sufficiently mature to be transferred by NASA, which means that it requires significant investment, expertise, and time to develop. Space entities are focused on rapid development with an emphasis on manufacturing and integration innovation with reduced cost and schedule and quick entrance into the market. Thermal Protection Systems (TPS) are mission critical, but their development takes years, and involve access to arc jets or unique test facilities. Therefore, their development is both risky and investment heavy. NASA ARC developed several new TPS materials over the last decade (C-PICA, HEEET, 3MDCP, 3DMAT, ADEPT woven TPS) and brought them to high TPS maturity, making them enablers for commercials space missions from LEO, Lunar Sample Return, Mars, and Venus missions. LEO missions are relevant to future Mars missions due to the comparable entry conditions. External Partners' Missions: C-PICA is a recent improvement on NASA’s heritage PICA lightweight TPS ablator. C-PICA is now considered an enabling technology for New Frontiers and other NASA missions. C-PICA was infused into several missions from external partners. Varda Space Industries’ Winnebago-1 spacecraft successfully returned to Earth from LEO on Feb. 21st, 2024, using a C-PICA heatshield. Inversion Space’s Ray vehicle will test both ARC’s C-PICA and SIRCA TPS materials on a LEO return mission later in 2024. The Kentucky Re-Entry Probe Experiment (KREPE) is another example of a low-cost flight experiment to demonstrate the use of small entry capsules to gather data with three instrumented Kentucky Re-entry and Universal Payload System (KRUPS) capsules. NASA Arc provided C-PICA and Soft-PICA for two of the next KRUPS capsules scheduled to re-enter Earth from the ISS later in 2024. Finally, Rocket Lab’s low-cost mission to Venus, scheduled to launch in December 2024, will search for habitable conditions in Venus’ cloud layer, making use of NASA ARC provided HEEET insulation layer heat shield, and SIRCA backshell TPS materials. Future NASA Missions: NASA’s ability to help commercial missions can lead to future low-cost missions for several reasons: Competition encourages lower cost; technology maturation is now done at an integrated system level; and a common design architecture between commercial and scientific applications requires no specialized engineering design. From an engineering perspective, both of these commercial LEO capsules aforementioned are capable of a Mars entry; the commercial payload mut be replaced with as science payload. Finally, several NASA mission concepts, that could be candidates for future SIMPLEx program calls, such as VATMOS-SR and Nephele, both proposing to target the Venusian atmosphere, would make use of the HEEET insulation layer TPS for part of their heat shield.

TPS materials↗

NASA NTRSDate not supplied

Recent Developments of Thermal Protection Materials to Enable Lower Cost Space Missions

Introduction: Starting with the Commercial Crew Program, a new paradigm has emerged at NASA. Rather than designing rockets and spacecrafts for every mission optimized to achieve science, NASA has begun to use a service-based model and utilizing public-private partnership in developing the vehicles that can bring broader benefits as well as lower the cost for NASA missions. Commercial companies own and operate those vehicles. This allows NASA to not design missions from the bottom up, and has cost, risk, and schedule savings implications. On the other side, the constraints require meeting the requirements in terms of mass, volume, power, etc. By leveraging NASA developed technologies, commercial companies can quickly demonstrate the commercial mission concept, and, through technology transfer, adopt needed technology to address supply chain problems. A downside is that the technology has to be sufficiently mature to be transferred by NASA, which means that it requires significant investment, expertise, and time to develop. Space entities are focused on rapid development with an emphasis on manufacturing and integration innovation with reduced cost and schedule and quick entrance into the market. Thermal Protection Systems (TPS) are mission critical, but their development takes years, and involve access to arc jets or unique test facilities. Therefore, their development is both risky and investment heavy. NASA ARC developed several new TPS materials over the last decade (C-PICA, HEEET, 3MDCP, 3DMAT, ADEPT woven TPS) and brought them to high TPS maturity, making them enablers for commercials space missions from LEO, Lunar Sample Return, Mars, and Venus missions. LEO missions are relevant to future Mars missions due to the comparable entry conditions. External Partners' Missions: C-PICA is a recent improvement on NASA’s heritage PICA lightweight TPS ablator. C-PICA is now considered an enabling technology for New Frontiers and other NASA missions. C-PICA was infused into several missions from external partners. Varda Space Industries’ Winnebago-1 spacecraft successfully returned to Earth from LEO on Feb. 21st, 2024, using a C-PICA heatshield. Inversion Space’s Ray vehicle will test both ARC’s C-PICA and SIRCA TPS materials on a LEO return mission later in 2024. The Kentucky Re-Entry Probe Experiment (KREPE) is another example of a low-cost flight experiment to demonstrate the use of small entry capsules to gather data with three instrumented Kentucky Re-entry and Universal Payload System (KRUPS) capsules. NASA Arc provided C-PICA and Soft-PICA for two of the next KRUPS capsules scheduled to re-enter Earth from the ISS later in 2024. Finally, Rocket Lab’s low-cost mission to Venus, scheduled to launch in December 2024, will search for habitable conditions in Venus’ cloud layer, making use of NASA ARC provided HEEET insulation layer heat shield, and SIRCA backshell TPS materials. Future NASA Missions: NASA’s ability to help commercial missions can lead to future low-cost missions for several reasons: Competition encourages lower cost; technology maturation is now done at an integrated system level; and a common design architecture between commercial and scientific applications requires no specialized engineering design. From an engineering perspective, both of these commercial LEO capsules aforementioned are capable of a Mars entry; the commercial payload mut be replaced with as science payload. Finally, several NASA mission concepts, that could be candidates for future SIMPLEx program calls, such as VATMOS-SR and Nephele, both proposing to target the Venusian atmosphere, would make use of the HEEET insulation layer TPS for part of their heat shield.

TPS materials↗