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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 613 records · Page 34

International Space Station Passive Thermal Control System Top Ten Lessons-Learned

Final document not an Abstract attached. The International Space Station (ISS) has been on-orbit for nearly 20 years, and there have been numerous technical challenges along the way from design to assembly to on-orbit anomalies and repairs. The Passive Thermal Control System (PTCS) management team has been a key player in successfully dealing with these challenges. The PTCS team performs thermal analysis in support of design and verification, launch and assembly constraints, integration, sustaining engineering, failure response, and model validation. This analysis is a significant body of work and provides a unique opportunity to compile a wealth of real world engineering and analysis knowledge and the corresponding lessons-learned. The PTCS lessons encompass the full life cycle of flight hardware from design to on-orbit performance and sustaining engineering. These lessons can provide significant insight for new projects and programs. Key areas to be presented include thermal model fidelity, verification methods, analysis uncertainty, and operations support.

Iovine, John V.↗

Prediction for Pressure Differential Across HEPA Filter Media Based on Media Characteristics and Particle Size Distribution

A new method for predicting the pressure drop across High Efficiency Particulate Air (HEPA) filter media is proposed based upon mass deposited onto the filter and known physical characteristics of the filter media. Detailed are the methods used in conjunction with current filter loading models to predict the pressure drop, as well as tests conducted to validate the methods. The benefit of a prediction model for practical use lies in the manufacturing and service life of nuclear grade HEPA filters. HEPA filters for use in nuclear facilities have a prescribed expiration date and a maximum allowable operating pressure drop. Therefore, the ability to predict the pressure drop across a filter and relate it to an expected length of service time can enable a reduction in wasted filters. This will allow for more informed decisions to be made based upon the dictated life cycle of the filters. Also, understanding and predicting how the pressure drop of HEPA filter media behaves as a function of physical characteristics and loaded mass can assist in future design and manufacturing of filter media. Currently, most existing pressure drop models are either computationally based or analytical methods relying on data gathered during tests. Neither are practical for prediction; the computational methods are difficult to implement, and the current analytical methods are more useful as tools for analysis. The current analytical model developed by Bergman et al. is based upon the pressure drop from each media fiber and modeling the deposited particles as newly formed fibers. Using Bergman's model and the media properties, air properties, and known aerosol particle size distribution, a pressure drop curve as a function of loaded mass can be created. This curve implies initial loading in the depth of the filter media with a transition to pure surface loading on the filter face, and a sensitivity to an evolving particle size distribution as mass continues to load onto the filter. To implement the predictive model, knowledge of the mean filter fiber diameter and porosity of the filter media is required. Traditionally, the mean fiber diameter is calculated as an effective diameter from prior media testing, however, in this study a Scanning Electron Microscope (SEM) technique is used to acquire this variable. Validation of the predictive model is provided by flat sheet media tests under a controlled environment with a measured particle size distribution of the challenge aerosol and shows reasonable preliminary agreement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

BISON validation of FeCrAl cladding mechanical failure during simulated reactivity-initiated accident conditions*

Here, a reactivity-initiated accident (RIA) is a postulated design basis accident in light water reactors (LWRs) in which a rapid reactivity insertion induces a fission rate increase and a fuel pellet temperature rise. During RIA, the fuel pellet thermally expands and may cause pellet-cladding mechanical interaction (PCMI). Separate effects PCMI tests were performed on C26M FeCrAl cladding tube samples, introducing biaxial stress via a well understood modified burst test (MBT) system. A high-speed camera in the MBT system captured the projections, covering a 360° view of the cladding deformation and enabling a digital image correlation (DIC) method to quantify the surface strains with high fidelity. Representative hot zero-power RIA mechanical loading conditions were applied to the sample, and the test duration ranged from 20 to 500 ms at an average temperature of 573 K. BISON finite element–based fuel performance code modeling was performed against the high-fidelity DIC data produced from the MBTs. Validation calculations were conducted with 2D models and systematically compared with test data of the burst time, burst pressure, burst hoop strains, and hoop strain rates. Based on the behaviors from the separate effects test, BISON calculations satisfactorily predicted the cladding deformation behaviors. Sensitivity analysis was conducted to identify highly influential mechanical properties responsible for the cladding failure behavior during the MBT experiments. The results highlight the significance of the cladding's mechanical strength in governing cladding strain, followed by the significance of the mechanical interactions between the pellet and the cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analysis of Smart Composite Structures Including Debonding

Smart composite structures with distributed sensors and actuators have the capability to actively respond to a changing environment while offering significant weight savings and additional passive controllability through ply tailoring. Piezoelectric sensing and actuation of composite laminates is the most promising concept due to the static and dynamic control capabilities. Essential to the implementation of these smart composites are the development of accurate and efficient modeling techniques and experimental validation. This research addresses each of these important topics. A refined higher order theory is developed to model composite structures with surface bonded or embedded piezoelectric transducers. These transducers are used as both sensors and actuators for closed loop control. The theory accurately captures the transverse shear deformation through the thickness of the smart composite laminate while satisfying stress free boundary conditions on the free surfaces. The theory is extended to include the effect of debonding at the actuator-laminate interface. The developed analytical model is implemented using the finite element method utilizing an induced strain approach for computational efficiency. This allows general laminate geometries and boundary conditions to be analyzed. The state space control equations are developed to allow flexibility in the design of the control system. Circuit concepts are also discussed. Static and dynamic results of smart composite structures, obtained using the higher order theory, are correlated with available analytical data. Comparisons, including debonded laminates, are also made with a general purpose finite element code and available experimental data. Overall, very good agreement is observed. Convergence of the finite element implementation of the higher order theory is shown with exact solutions. Additional results demonstrate the utility of the developed theory to study piezoelectric actuation of composite laminates with pre-existing debonding. Significant changes in the modes shapes and reductions in the control authority result due to partially debonded actuators. An experimental investigation addresses practical issues, such as circuit design and implementation, associated with piezoelectric sensing and actuation of composite laminates. Composite specimens with piezoelectric transducers were designed, constructed and tested to validate the higher order theory. These specimens were tested with various stacking sequences, debonding lengths and gains for both open and closed loop cases. Frequency changes of 15% and damping on the order of more than 20% of critical damping, via closed loop control, was achieved. Correlation with the higher order theory is very good. Debonding is shown to adversely affect the open and closed loop frequencies, damping ratios, settling time and control authority.

Chattopadhyay, Aditi↗

Test and Analysis of the 8-foot Diameter Cylindrical Sandwich Composite Test Article CTA8.2B: As part of the NASA Engineering and Safety Center Shell Buckling Knockdown Factor Project

The buckling response of thin-walled cylindrical structures have long been shown to be sensitive to various imperfections. That is, imperfections related to load introduction, boundary conditions, material property variation, and geometric deviations can all contribute to experimentally obtained buckling loads being lower than the buckling loads predicted for perfect representations of the same thin-walled cylindrical structure. To account for the influence of geometry-based imperfections of a thin-walled cylindrical structure on buckling response, a design factor (also known as a buckling knockdown factor) is used during the design phase. Guidelines for buckling knockdown factors are readily available in NASA SP-8007, Buckling of Thin Walled Circular Cylinders, which was updated in 2020. Prior to this recent update, NASA SP-8007 had not been updated since 1969, and since that time, computational analysis, experimental testing, and manufacturing methods have significantly improved. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF, NESC Assessment 07-010-E) had the goal of developing buckling design recommendations for select classes of metallic and composite launch-vehicle structures [3]. Specifically, the test and analysis results from the fourth SBKF composite test article SBKF-P3-CYL-CTA8.2B, which is referred to as CTA8.2B, are described in this paper. This test was the fourth in a series of four tests on sandwich composite cylinders that will be used to experimentally validate analysis methods, which in turn can be used to develop new analysis-based shell buckling design guidelines for typical sandwich composite launch vehicle cylindrical structures. Publications describing previous test validation with analysis are available in Refs. CTA8.2B was designed to occupy one corner of the design space with approximately equal bending stiffnesses in the axial and transverse directions and have a larger ratio of radius to effective shell thickness. Each test article had a unique design and was designed to occupy a specific region of the design space. CTA8.2B was an 8-foot diameter honeycomb-core sandwich cylinder that was fabricated and tested at the NASA Marshall Space Flight Center (MSFC). The primary objectives of this test were to interrogate the structural capability of a composite test article, and to verify the test article design and analysis approach for cylinders subjected to axial compression and combined axial and bending loads. First, descriptions of the test article design and test are given in Section 2.0, and modeling and analysis methods used in support of the test article design and testing activities are described briefly in Section 3.0. Then, select test results are presented and compared to predicted results in Section 4.0, and concluding remarks are presented in Section 5.0. Finally, drawings of CTA8.2B and references used to support the test and analysis are provided in the Appendix.

Nonlinear analysis↗

Verification and Validation of a Conceptual Model of the Auto-Rigging Payload Handling and Off-Loading System Using LEGO Technic System and Three-Dimensional Printed Parts

A conceptual model (CM) can be used to validate a concept in modeling and simulation life cycles. During the 2020-2022 Coronavirus disease 2019 (COVID-19) pandemic, for employee safety NASA implemented center closures and mandatory telework for the entire workforce. During this challenging time, engineers and researchers at NASA Langley Research Center (LaRC) looked for safe and innovative approaches and methods to continue the development of CMs for various projects. Engineers and researchers at LaRC researched Auto-Rigging Payload Handling and Off-Loading System (ARPHOLS) for payload handing and off-loading a system on an inclined lunar lander deck. In this paper, the development of a CM and the verification and validation of a conceptual idea for ARPHOLS using a LEGO Technic system and three-dimensional printed parts is presented.

Design↗

Advanced Models and Fast Simulation Algorithms for MARS Plants

With the successful commercialization of modular multilevel converters (MMC) and rapid increase in photovoltaic (PV) penetration and energy storage systems (ESS), one of the research areas being explored dynamically is integration of PV systems and ESS systems to MMCs. On this front, an integrated development of PV plants, ESS, and alternating- and direct-current (ac/dc) systems through Multi-Port Autonomous Reconfigurable Solar (MARS) plant is proposed and being researched upon. However, simulation of MARS systems on traditional existing software takes very long time (order of days) due to the presence of a large number of states and non-linear devices. Therefore, development of fast high fidelity models is of paramount importance to test the hardware design, control design and planning of power system expansions. In this context, two research objectives are addressed in this paper: firstly, an ultra fast single- or multi- CPU simulation algorithm to simulate the MARS system based on state-space models, hybrid discretization algorithm with a relaxation technique that reduces the imposed computational burden and a multi-rate method is presented. Secondly, a reduced order model of MARS is also presented. Both the developed techniques are validated with respect to reference PSCAD/EMTDC model.

Marthi, Phani Ratna Vanamali↗

High-Performance Modeling and Simulation of Anchoring in Granular Media for NEO Applications

NASA is interested in designing a spacecraft capable of visiting a near-Earth object (NEO), performing experiments, and then returning safely. Certain periods of this mission would require the spacecraft to remain stationary relative to the NEO, in an environment characterized by very low gravity levels; such situations require an anchoring mechanism that is compact, easy to deploy, and upon mission completion, easy to remove. The design philosophy used in this task relies on the simulation capability of a high-performance multibody dynamics physics engine. On Earth, it is difficult to create low-gravity conditions, and testing in low-gravity environments, whether artificial or in space, can be costly and very difficult to achieve. Through simulation, the effect of gravity can be controlled with great accuracy, making it ideally suited to analyze the problem at hand. Using Chrono::Engine, a simulation pack age capable of utilizing massively parallel Graphic Processing Unit (GPU) hardware, several validation experiments were performed. Modeling of the regolith interaction has been carried out, after which the anchor penetration tests were performed and analyzed. The regolith was modeled by a granular medium composed of very large numbers of convex three-dimensional rigid bodies, subject to microgravity levels and interacting with each other with contact, friction, and cohesional forces. The multibody dynamics simulation approach used for simulating anchors penetrating a soil uses a differential variational inequality (DVI) methodology to solve the contact problem posed as a linear complementarity method (LCP). Implemented within a GPU processing environment, collision detection is greatly accelerated compared to traditional CPU (central processing unit)- based collision detection. Hence, systems of millions of particles interacting with complex dynamic systems can be efficiently analyzed, and design recommendations can be made in a much shorter time. The figure shows an example of this capability where the Brazil Nut problem is simulated: as the container full of granular material is vibrated, the large ball slowly moves upwards. This capability was expanded to account for anchors of different shapes and penetration velocities, interacting with granular soils.

Quadrelli, Marco B.↗

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Tracking the ancestry of known and ‘ghost’ homeologous subgenomes in model grass Brachypodium polyploids

Unraveling the evolution of plant polyploids is a challenge when their diploid progenitor species are extinct or unknown or when genome sequences of known progenitors are unavailable. Existing subgenome identification methods cannot adequately infer the homeologous genomes that are present in the allopolyploids if they do not take into account the potential existence of unknown progenitors. We addressed this challenge in the widely distributed dysploid grass genus Brachypodium, which is a model genus for temperate cereals and biofuel grasses. We used a transcriptome-based phylogeny and newly designed subgenome detection algorithms coupled with a comparative chromosome barcoding analysis. Our phylogenomic subgenome detection pipeline was validated in Triticum allopolyploids, which have known progenitor genomes, and then used to infer the identities of three subgenomes derived from extant diploid species and four subgenomes derived from unknown diploid progenitors (ghost subgenomes) in six Brachypodium polyploids (B. mexicanum, B. boissieri, B. retusum, B. phoenicoides, B. rupestre and B. hybridum), of which five contain undescribed homeologous subgenomes. The existence of the seven Brachypodium progenitor genomes in the polyploids was confirmed by their karyotypic barcode profiles. Comparative phylogenomics of nuclear versus plastid trees allowed us to formulate hypothetical homoploid hybridizations and allo- and autopolyploidization scenarios that could have generated the six Brachypodium polyploids.

59 BASIC BIOLOGICAL SCIENCES↗

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning

Computational models that formalize complex human behaviors enable study and understanding of such behaviors. However, collecting behavior data required to estimate the parameters of such models is often tedious and resource intensive. Thus, estimating dataset size as part of data collection planning (also known as Sample Size Determination) is important to reduce the time and effort of behavior data collection while maintaining an accurate estimate of model parameters. In this paper, we present a sample size determination method based on Uncertainty Quantification (UQ) for a specific Inverse Reinforcement Learning (IRL) model of human behavior, in two cases: 1) pre-hoc experiment design—conducted in the planning stage before any data is collected, to guide the estimation of how many samples to collect; and 2) post-hoc dataset analysis—performed after data is collected, to decide if the existing dataset has sufficient samples and whether more data is needed. Here, we validate our approach in experiments with a realistic model of behaviors of people with Multiple Sclerosis (MS) and illustrate how to pick a reasonable sample size target. Our work enables model designers to perform a deeper, principled investigation of effects of dataset size on IRL.

97 MATHEMATICS AND COMPUTING↗

HSR combustion analytical research

Increasing the pressure and temperature of the engines of a new generation of supersonic airliners increases the emissions of nitrogen oxides (NO(x)) to a level that would have an adverse impact on the Earth's protective ozone layer. In the process of evolving and implementing low emissions combustor technologies, NASA LeRC has pursued a combustion analysis code program to guide combustor design processes, to identify potential concepts of the greatest promise, and to optimize them at low cost, with short turnaround time. The computational analyses are evaluated at actual engine operating conditions. The approach is to upgrade and apply advanced computer programs for gas turbine applications. Efforts were made in further improving the code capabilities for modeling the physics and the numerical methods of solution. Then test cases and measurements from experiments are used for code validation.

Nguyen, H. Lee↗

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.

Lim, Kyong B.↗

Force Limited Vibration Testing

This slide presentation reviews the concept and applications of Force Limited Vibration Testing. The goal of vibration testing of aerospace hardware is to identify problems that would result in flight failures. The commonly used aerospace vibration tests uses artificially high shaker forces and responses at the resonance frequencies of the test item. It has become common to limit the acceleration responses in the test to those predicted for the flight. This requires an analysis of the acceleration response, and requires placing accelerometers on the test item. With the advent of piezoelectric gages it has become possible to improve vibration testing. The basic equations have are reviewed. Force limits are analogous and complementary to the acceleration specifications used in conventional vibration testing. Just as the acceleration specification is the frequency spectrum envelope of the in-flight acceleration at the interface between the test item and flight mounting structure, the force limit is the envelope of the in-flight force at the interface . In force limited vibration tests, both the acceleration and force specifications are needed, and the force specification is generally based on and proportional to the acceleration specification. Therefore, force limiting does not compensate for errors in the development of the acceleration specification, e.g., too much conservatism or the lack thereof. These errors will carry over into the force specification. Since in-flight vibratory force data are scarce, force limits are often derived from coupled system analyses and impedance information obtained from measurements or finite element models (FEM). Fortunately, data on the interface forces between systems and components are now available from system acoustic and vibration tests of development test models and from a few flight experiments. Semi-empirical methods of predicting force limits are currently being developed on the basis of the limited flight and system test data. A simple two degree of freedom system is shown and the governing equations for basic force limiting results for this system are reviewed. The design and results of the shuttle vibration forces (SVF) experiments are reviewed. The Advanced Composition Explorer (ACE) also was used to validate force limiting. Test instrumentation and supporting equipment are reviewed including piezo-electric force transducers, signal processing and conditioning systems, test fixtures, and vibration controller systems. Several examples of force limited vibration testing are presented with some results.

random vibration testing↗

Open Rotor Noise Shielding by Blended-Wing-Body Aircraft

This paper presents an analysis of open rotor noise shielding by Blended Wing Body (BWB) aircraft by using model scale test data acquired in the Boeing Low Speed Aeroacoustic Facility (LSAF) with a legacy F7/A7 rotor model and a simplified BWB platform. The objective of the analysis is the understanding of the shielding features of the BWB and the method of application of the shielding data for noise studies of BWB aircraft with open rotor propulsion. By studying the directivity patterns of individual tones, it is shown that though the tonal energy distribution and the spectral content of the wind tunnel test model, and thus its total noise, may differ from those of more advanced rotor designs, the individual tones follow directivity patterns that characterize far field radiations of modern open rotors, ensuring the validity of the use of this shielding data. Thus, open rotor tonal noise shielding should be categorized into front rotor tones, aft rotor tones and interaction tones, not only because of the different directivities of the three groups of tones, but also due to the differences in their source locations and coherence features, which make the respective shielding characteristics of the three groups of tones distinctly different from each other. To reveal the parametric trends of the BWB shielding effects, results are presented with variations in frequency, far field emission angle, rotor operational condition, engine installation geometry, and local airframe features. These results prepare the way for the development of parametric models for the shielding effects in prediction tools.

Guo, Yueping↗

Additional Findings from the Common Research Model Natural Laminar Flow Wind Tunnel Test

An experimental investigation of the Common Research Model with Natural Laminar Flow (CRM-NLF) took place in the National Transonic Facility (NTF) at the NASA Langley Research Center in 2018. The 5.2% scale semispan model was designed using a new natural laminar flow design method, Crossflow Attenuated NLF (CATNLF). CATNLF enables laminar flow on typical transport wings with high sweep and Reynolds number by reshaping the wing airfoils to obtain specific pressure distribution characteristics that control the crossflow growth near the leading edge. The CATNLF method also addresses Tollmien- Schlichting transition, attachment line transition, and Görtler vortices. During the wind tunnel test, data were acquired to address three primary test objectives: validate the CATNLF design method, characterize the NTF laminar flow testing capabilities, and establish best practices for laminar flow wind tunnel testing. The present paper provides both experimental and computational data to understand the CRM-NLF laminar flow characteristics, as well as address the three primary test objectives. The effects of angle of attack and Reynolds number on the CRM-NLF laminar flow extent are studied, and the dominant transition mechanism is evaluated at a variety of test conditions. Critical N-factors are calculated for the NTF environment, and a discussion on best practices for laminar flow wind tunnel testing is provided. The CRM-NLF in the NTF provided initial confirmation of the ability of the CATNLF method to suppress crossflow growth and enable significant extents of laminar flow on transport wings with high sweep and Reynolds numbers.

Lynde, Michelle N.↗

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗

Seismic signal augmentation to improve generalization of deep neural networks

Deep learning has emerged as an effective approach for seismic data processing in general, and for earthquake monitoring in particular. The ability of deep learning models to generalize beyond the training and validation data is important for comprehensive earthquake monitoring; this ability furthermore depends on the availability of a sufficiently large and complete training dataset. However, this requirement can prove challenging to meet due to significant effort and time for data collection and labeling. Data augmentation provides an efficient and effective approach for increasing the dimension of training samples and improving generalization to unseen samples. In this paper, we present augmentation methods appropriate for seismic waveforms and demonstrate their ability to reduce bias and increase performance. Furthermore, these augmentation methods can be applied to a wide range of deep learning applications designed for seismic data.

58 GEOSCIENCES↗