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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 955 records · Page 53

Improving Structural Test and Analysis Correlation Using Digital Image Correlation Boundary Measurements

Simplified idealizations, such as clamped or simply supported, are commonly used as support boundary conditions in modeling and analysis of tested aerospace structures. However, these simplifications are not always appropriate and characterization of the response of non-rigid boundaries is often required to improve test and analysis correlation. While e analysis models are typically modified to better represent the test, this modification is often not practical due to the complexities of the boundary response. A study is conducted to examine the use of digital image correlation (DIC) to measure the boundary support structure response and then to adjust the test data to remove the effects of the boundary response in order to improve test and analysis correlation. A high-aspect ratio composite wing test is the subject of the study. Three sources of boundary flexibility contributing to rigid body rotation of the test wing are identified and quantified using both DIC and conventional test data. The wing displacement test data are adjusted using DIC data for these sources. Wing displacement test data is also adjusted using direct measurement of wing rotation from a DIC system that monitored the top surface, root region of the wing, and using available conventional instrumentation. The adjusted data exhibits improved test and analysis correlation and demonstrated the benefit of using DIC along with conventional instrumentation to collect and interpret test data.

Andrew E Lovejoy↗

3-Dimensional Advanced Workflow

Have you ever been frustrated with the 2-dimensional nature of implementing complex Advanced Workflows (AWF) in your RSA Archer environment? Does the lack of concurrent, parallel workflows make you scratch your head and ask, ‘Why?’ Has your AWF gotten so complicated and convoluted that navigating through a maze-like plate of spaghetti looks simple and straightforward by comparison? If so, come listen to how NASA leverages Questionnaires to add an extra dimension and welcome simplification to complex Advanced Workflow configurations!

RSA Archer↗

Precision Projector Laboratory: Detector Characterization with an Astronomical Emulation Testbed

As astronomical observations benefit from improved sensitivity, the effectiveness of scientific programs is becoming limited by systematics that often originate in poorly understood image sensor behavior. Traditional, bottom-up detector characterization methods provide one way to model underlying detector physics, and generate ever more faithful numerical simulations, but this approach is vulnerable to preconceptions and over-simplification. The alternative top-down approach is laboratory emulation, which enables observation, calibration, and analysis scenarios to be tested without relying on a complete understanding of the underlying physics. This complements detector characterization and simulation efforts by testing their validity. We describe a laboratory facility and experimental testbed that supports the emulation of a wide range of mission concepts such as gravitational weak lensing measurements by WFIRST and high precision spectrophotometry of transiting exoplanets by JWST. An Offner relay projects readily customizable "scenes" (e.g. stars, galaxies, spectra) with very low optical aberration over the full area of a typical optical or near infrared image sensor. f/8 and slower focal ratios may be selected, spanning those of most proposed space missions and approximating the point spread function (PSF) size of seeing limited ground based surveys. Diffraction limited PSFs are projected over a wide field of view and wavelength range to deliver highly predictable image patterns down to sub-pixel scales with stable intensity and fine motion control. The testbed enables realistic validation of detector performance on science-like images, which aids mission design and survey strategy, as well as targeted investigations of various detector effects.

Seshadri, Suresh↗

Physics and Chemistry of Te and HgTe-based Ternary Melts

Historically, the theoretical treatment of the liquid phases has always been more difficult and complicated than that for solid and gas phases. A liquid has no lattice structure as crystalline solids and the atoms/molecules in the liquid can migrate through it relatively rapidly. On the other hand, it is also interacting with many other atoms/molecules so that the simplifications of the kinetic theory of gases cannot be employed. For more complicated liquids, such as the liquids of high ionicity and those containing hydrogen bonds and electric dipoles, the understanding is far from complete. At the same time, accurate information on the physics and chemistry of semiconductor melts is needed for the quantitative descriptions of the process of crystal growth from melt. The pre-crystallization phenomena in the liquid phase are critical because the properties of the grown crystals depend on the state and structure of the melt as well as the thermal history of the melt during solidification process. However, the data on the liquid phase, such as thermophysical properties of semiconductor melts are scarce, especially for the HgTe-based II-VI ternary compound semiconductors because of their high vapor pressure and extreme toxicity. Analysis of the thermophysical properties of the melt can provide information about structural transitions of the melt during the solidification process. From a broader point of view, the structure of liquids is much more complicated than the crystalline solids, especially the relaxation behavior through different thermal histories. The theory of hetero-phase fluctuations of liquids is applicable to any many-body systems including condensed-matter physics, field theory, physics of nuclear-matter, cosmology, biology and even sociology. This book summarizes the physics and chemistry from the experimental measurements and theoretical analyses of phase diagram, thermodynamic properties, density, thermal conductivity, viscosity, and electrical conductivity on the binary, pseudo-binary and ternary melts of the most advanced IR-detector material systems of HgCdTe and HgZnTe as well as the analyses of these results. The main objectives of this study are: (1) to provide the phase diagrams and thermodynamic properties of Hg-Cd-Te and Hg-Zn-Te systems through quantitatively fitting the experimental data by assuming an associated solution model for the liquid phase, (2) to experimentally measure the thermophysical properties of the Hg-Cd-Te and Hg-Zn-Te melts, including density, viscosity, electrical conductivity and thermal conductivity as functions of temperature and composition and (3) to enhance the fundamental knowledge of hetero-phase fluctuations and relaxation phenomena in the melts and extend our understanding of the solidification process in order to interpret the experimental results of crystal growth so as to improve the melt growth processes of the compound semiconductor. The physics and chemistry of Te and HgTe-based ternary melts were explored through the studies of the structural transformation during melting, the supercooling during solidification, the relaxation phenomena after rapid cooling of the melts and the metal-semiconductor transition in the melts through the analyses of electrical conductivity and Lorenz number. An in-depth study on the thermophysical properties and their time-dependent structural dynamic processes taking place in the vicinity of the solid-liquid phase transition of the narrow homogeneity range HgTe-based ternary semiconductors as well as the analysis of the homogenization process in the melt will also be presented.

Thermophysical properties↗

Design of 1 kW Simplified Stirling Controller Using Capacitor-Based Power Factor Correction

Free-piston Stirling convertors hold potential for efficient, reliable thermal to electric power conversion, provided they are paired with a robust controller. This paper outlines work underway on a system-level optimization of a kW controller. Using simplified control and passive power factor correction (PFC) this design explores the possibility of reducing programmatic risk through system simplification. Efficiency is improved through incorporating wide-bandgap gallium nitride (GaN) switches, and PFC volume is minimized through the use of polymer multi-layer capacitors. This work is aimed at exploring new approaches for future Stirling space power concepts.

Stirling↗

Optimization, Design, and Demonstration of 1 kW Stirling Controller Using Capacitor-based Power Factor Correction

Free-piston Stirling convertors provide efficient, reliable thermal to electric power conversion, provided they are paired with a reliable controller. This paper outlines work underway on design concepts for kilowatt-class controllers. Using passive power factor correction (PFC) this design explores the possibility of reducing programmatic risk through system simplification. Efficiency is maximized through incorporating wide-bandgap gallium nitride (GaN) switches, and passive PFC volume is minimized through the use of polymer multi-layer capacitors. This work is aimed at exploring new approaches for future Stirling controllers.

Christopher Barth↗

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗

Impact of Thermochromic Coatings on Thermal Management for Human Spacecraft Applications

Thermochromic variable emittance coatings (VECs) allow for passive, dynamic thermal management of space vehicles due to their temperature dependent optical properties. Ideally, a thermochromic material should exhibit low mid-IR emissivity for lower temperatures and switch to high mid-IR emissivity for higher temperatures; one promising material that demonstrates these characteristics is Lanthanum Strontium Manganite (LSM). The transition temperatures of LSM are dependent on the Lanthanum-to-Strontium ratio x, La1-xSrxMnO3. La0.8Sr0.2MnO3, which has an emittance of 0.5 for < 270 K, then a linear increase in emittance to 0.8 over an increase of 70 K where it will saturate at ~340K, is commonly utilized but this is tunable by changing the Sr concentration. The tunability of the transition temperature range of LSM motivates a need to understand the optimal thermal transition range for human spacecraft. Additionally, LSM has high solar absorptance and to combat this issue the VEC will be micropatterned on top of a highly solar reflective layer of Barium Sulfate (BaSO4). Consequently, this work will elucidate the tradeoffs between solar absorptance and variable emittance for this technology since the micropattern adversely couples the solar absorptance to the mid-IR emittance. This work develops a computational model using Thermal Desktop to study the utility of VECs on human spacecraft, such as Orion, subjected to mission phases such as lunar transit and Gateway docking. The model considers both external heat loads, from solar irradiation and planetary IR, as well as vehicle heat loads, from avionics and crew, as an input into the body mounted thermochromic radiators. There are several design targets for VECs, i.e. achieving the largest change in emittance, finding the optimal temperature range for the transition, and achieving the highest emittance in the high temperature phase. This work prioritizes these design targets for LSM to achieve the optimal heat rejection for a human spacecraft. The VECs are compared with static emittance coatings and the efficiency gains are quantified. Thermochromic VECs will ultimately lead to simplifications of active cooling systems which synergistically correlates to mass reduction and less energy consumption for space vehicles.

Joseph Peoples↗

Preventing Anomalous Torques in Circumbinary Accretion Simulations

Numerical experiments are the primary method of studying the evolution of circumbinary disks due to the strong nonlinearities involved. Many circumbinary simulations also require the use of numerical mass sinks: source terms that prevent gas from unphysically accumulating around the simulated point masses by removing gas at a given rate. However, special care must be taken when drawing physical conclusions from such simulations to ensure that results are not biased by numerical artifacts. We demonstrate how improved sink methods reduce some of these biases, using simulations of aspect ratio 0.1 accretion disks around binaries with mass ratios between 0.1 and 1. We show that sink terms that do not reduce the angular momentum of gas relative to the accreting object (1) reduce the dependence on the sink rate of quantities such as the torque on the binary, distribution of accretion between binary components, and evolution of the binary semimajor axis; (2) reduce the degree to which the sink rate affects the structure of the accretion disks around each binary component; (3) alter the variability of accretion onto the binary, regularizing it in time. We also investigate other potential sources of systematic error, such as gravitational softening and simplifications to the viscous stress tensor. Because of the strong dependence of binary orbital evolution on both the torque and the distribution of mass between binary components, the sink method influences the orbital evolution of the binary at all mass ratios, with mass ratios below ∼0.3 most affected.

Alexander Dittmann↗

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

G F Bomarito↗

Reducing Risk of InSight Surface Operations Through High-Fidelity Command Sequence Modeling

Simulating spacecraft behavior is crucial for the success of deep space missions, and failure to do so may result in damages to or the loss of the spacecraft. Many previous deep space missions have made use of ground-simulation of sequenced commanding, at speeds far greater than real time, to predict spacecraft state over time through the execution of onboard sequences. This type of modeling can be done at any fidelity, and most missions have opted to decrease fidelity to reduce cost and complexity. However, NASA’s Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission expanded the scope of ground modeling considerably, which has led to numerous benefits over past implementations. This paper will discuss the process and products that InSight created, as well as the lessons learned from successfully operating the spacecraft on Mars. InSight is the first JPL mission to expand the scope of ground modeling to include the uplink of files from Earth to the spacecraft, rather than making the simplification that any command sequences already exist onboard the spacecraft. The advantages of modeling the uplink of files are numerous. First, it allows for accurate modeling of the onboard filesystem of the spacecraft at all points in time, meaning that all file loads and deletions throughout the mission are modeled at the exact moment they are predicted to actually happen. Second, operators can be more certain that dependencies between sequences are not broken due to the dynamic nature of the filesystem as files are deleted, copied, and uplinked. Lastly, spacecraft filesystem tracking allows for management of sequences prior to uplink, limiting the uplink to only new sequences. The onboard filesystem model became crucial to mission success, emphasizing the importance of investing in accurate models before the need for them arises. During daily tactical operations of a spacecraft on Mars, a model is only useful if the results can be interpreted quickly. In this fast-paced environment, it is essential that command products are modeled and reviewed, errors are found and diagnosed, and new command products are redelivered, remodeled, re-reviewed in a timely manner. It is impossible to review the entire model and therefore the results of the model must be condensed and presented in a fashion that is intuitive, easy-to-navigate, complete, and trustworthy. InSight developed a number of innovative sequence review products that are designed to provide operators with the information required to quickly assess the validity of command products and diagnose potential issues. Together, these products provide a complete, yet succinct picture of the command and sequence model to the operators and facilitate a quick assessment of all sequence command products. This paper will cover planning and sequencing innovations made during InSight surface operations, and will compare the tools, processes, and results to those on other missions. Additionally, the paper will cover the flexible, yet robust nature of the planning and sequencing system architecture and how that flexibility allowed for rapid development and response to the unpredictability of Mars.

Cloutier, Kyle↗

Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming

In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.

machine learning↗

Formal Analysis of the Compact Position Reporting Algorithm

This presentation documents the formal analysis of the compact position reporting (CPR) algorithm. CPR is a fundamental part of Automatic Dependent Surveillance - Broadcast (ADS-B), which is a global protocol for aircraft communication. The formal analysis found and corrected issues with the algorithm, proposed simplifications, and created a formally verified reference implementation, all of which are incorporated in the governing standards document.

Formal Methods↗

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

Uncertainty quantification↗

Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming

In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.

David Randall↗

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗

EMU Helmet Free Water Transport Assessment for the HAB 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. To assess the effectiveness of this strategy, a computational fluid dynamics (CFD) model of a human mannikin head in the EMU helmet was used to track water droplets and quantify how much water is likely to be caught by the absorbent material. A combination of engineering judgment, tests, and CFD results were used to develop the expected path of droplets in the helmet, to account for the simplifications necessary in modeling two-phase flow.

Abigail Rose Baukus↗

The 21-cm Signal From the Cosmic Dawn: Metallicity Dependence of High Mass X-Ray Binaries

X-rays from high-mass X-ray binaries (HMXBs) are likely the main source of heating of the intergalactic medium (IGM) during Cosmic Dawn (CD), before the completion of reionization. This Epoch of Heating (EoH; z ∼10–15) should soon be detected via the redshifted 21-cm line from neutral hydrogen, allowing us to indirectly study the properties of HMXBs in the unseen, first galaxies. Low-redshift observations, as well as theoretical models, imply that the integrated X-ray luminosity to star formation rate of HMXBs (L_X/SFR) should increase in metal-poor environments, typical of early galaxies. Here, we study the impact of the metallicity (Z) dependence of L_X/SFR during the EoH. For our fiducial models, galaxies with star formation rates of order 10^(−3)–10^(−1)M_⊙ yr^(−1) and metallicities of order 10^(−3) –10^(−2) Z_⊙ are the dominant contributors to the X-ray background (XRB) during this period. Different L_X/SFR–Z relations result in factors of ∼ 3 differences in these ranges, as well as in the mean IGM temperature and the large-scale 21-cm power, at a given redshift. We compute mock 21-cm observations adopting as a baseline a 1000 h integration with the upcoming Square Kilometer Array (SKA) for two different L_X/SFR–Z relations. We perform inference on these mock observations using the common simplification of a constant L_X/SFR, finding that constant L_X/SFR models can recover the IGM evolution of the more complicated L_X/SFR–Z simulations only during the EoH. At z < 10, where the typical galaxies are more polluted, constant L_X/SFR models overpredict the XRB and its relative contribution to the early stages of the reionization.

galaxies: high-redshift↗