Results for “TC plug”

NASA NTRS2015

Estimation of Surface Temperature and Heat Flux by Inverse Heat Transfer Methods Using Internal Temperatures Measured While Radiantly Heating a Carbon/Carbon Specimen up to 1920 F

The ability to solve the heat conduction equation is needed when designing materials to be used on vehicles exposed to extremely high temperatures; e.g. vehicles used for atmospheric entry or hypersonic flight. When using test and flight data, computational methods such as finite difference schemes may be used to solve for both the direct heat conduction problem, i.e., solving between internal temperature measurements, and the inverse heat conduction problem, i.e., using the direct solution to march forward in space to the surface of the material to estimate both surface temperature and heat flux. The completed research first discusses the methods used in developing a computational code to solve both the direct and inverse heat transfer problems using one dimensional, centered, implicit finite volume schemes and one dimensional, centered, explicit space marching techniques. The developed code assumed the boundary conditions to be specified time varying temperatures and also considered temperature dependent thermal properties. The completed research then discusses the results of analyzing temperature data measured while radiantly heating a carbon/carbon specimen up to 1920 F. The temperature was measured using thermocouple (TC) plugs (small carbon/carbon material specimens) with four embedded TC plugs inserted into the larger carbon/carbon specimen. The purpose of analyzing the test data was to estimate the surface heat flux and temperature values from the internal temperature measurements using direct and inverse heat transfer methods, thus aiding in the thermal and structural design and analysis of high temperature vehicles.

Pizzo, Michelle↗

NASA NTRSDate not supplied

Arc Jet Test Article Instrumentation

Explore the source record for details and available documents.

arc jet↗

NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗

NASA NTRSDate not supplied

The State of Cryptolib – The Open-Source Satellite Cryptography Library

What state would the world be in if all internet traffic was unencrypted? Imagine an alternate universe where you can plug a packet sniffing device into your home internet and capture the web traffic of the entire world. It seems obvious that this scenario is less than desirable. If we would not allow this for the internet, why would we allow this in the space domain? With the advent of open-source ground stations, commercial off the shelf hardware, and ground stations as a service, the barrier to entry for space communications is rapidly lowering. New players enter the space realm everydayevery day, and the presence of tools to allow apprentice evildoers the ability to exploit satellite communications is on the horizon. Not only are legacy missions at risk, but future missions are as well - particularly lower budget science missions with more stringent sciencesize, weight, and power constraints. that may find it difficult to utilize hardware-based encryption solutions. In terms of Civilian Aerospace, NASA Standard 1006 generally directs that missions "shall protect the command stack with encryption that meets or exceeds Federal Information Processing Standards (FIPS) 140". Fortunately, the Consultative Committee for Space Data Systems (CCSDS) has published an international standard on Space Data Link Security. The combination of these two forces has resulted in CryptoLib - an open-source, C-based, encryption library that aims to be CCSDS SDLS compliant. CryptoLib is designed to support smaller missions on a tight budget that may be subject to the more stringent command link encryption requirements. Additionally, CryptoLib serves as an underpinning in JPL's Key Management & Cryptography (KMC) suite and is also designed to function as a 'drop-in' for smaller missions. CryptoLib is in active development and currently provides Telecommand (TC), Telemetry (TM), and Advanced Orbiting Systems (AOS) encryption and decryption capabilities with a variety of encryption and authentication schemes. This presentation will report the latest features, current status, and future plans for CryptoLib.

open-source encryption↗

NASA NTRSDate not supplied

The State of CryptoLib – The Open-Source Satellite Cryptography Library

What state would the world be in if all internet traffic was unencrypted? Imagine an alternate universe where you can plug a packet sniffing device into your home internet and capture the web traffic of the entire world. It seems obvious that this scenario is less than desirable. If we would not allow this for the internet, why would we allow this in the space domain? With the advent of open-source ground stations, commercial off the shelf hardware, and ground stations as a service, the barrier to entry for space communications is rapidly lowering. New players enter the space realm everydayevery day, and the presence of tools to allow apprentice evildoers the ability to exploit satellite communications is on the horizon. Not only are legacy missions at risk, but future missions are as well - particularly lower budget science missions with more stringent sciencesize, weight, and power constraints. that may find it difficult to utilize hardware-based encryption solutions. In terms of Civilian Aerospace, NASA Standard 1006 generally directs that missions "shall protect the command stack with encryption that meets or exceeds Federal Information Processing Standards (FIPS) 140". Fortunately, the Consultative Committee for Space Data Systems (CCSDS) has published an international standard on Space Data Link Security. The combination of these two forces has resulted in CryptoLib - an open-source, C-based, encryption library that aims to be CCSDS SDLS compliant. CryptoLib is designed to support smaller missions on a tight budget that may be subject to the more stringent command link encryption requirements. Additionally, CryptoLib serves as an underpinning in JPL's Key Management & Cryptography (KMC) suite and is also designed to function as a 'drop-in' for smaller missions. CryptoLib is in active development and currently provides Telecommand (TC), Telemetry (TM), and Advanced Orbiting Systems (AOS) encryption and decryption capabilities with a variety of encryption and authentication schemes. This presentation will report the latest features, current status, and future plans for CryptoLib.

open-source encryption↗