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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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This viewgraph presentation reviews the interface force measurement at spacecraft separation of GLAST Delta II. The contents include: 1) Flight Force Measurement (FFM) Background; 2) Team Members; 3) GLAST Mission Overview; 4) Methodology Development; 5) Ground Test Validation; 6) Flight Data; 7) Coupled Loads Simulation (VCLA & Reconstruction); 8) Basedrive Simulation; 9) Findings; and 10) Summary and Conclusions.
A recent microstructure-based FEM model that couples crystal-based plasticity, the B2<-> MB190 phase transformation and anisotropic elasticity at the grain scale is calibrated to recent data for polycrystalline NiTi (49.9 at.% Ni). Inputs include anisotropic elastic properties, texture and differential scanning calorimetry data, as well as a subset of recent isothermal deformation and load-biased thermal cycling data. The model is assessed against additional experimental data. Several experimental trends are captured - in particular, the transformation strain during thermal cycling monotonically increases and reaches a peak with increasing bias stress. This is achieved, in part, by modifying the martensite hardening matrix proposed by Patoor et al. [Patoor E, Eberhardt A, Berveiller M. J Phys IV 1996;6:277]. Some experimental trends are underestimated - in particular, the ratcheting of macrostrain during thermal cycling. This may reflect a model limitation that transformation-plasticity coupling is captured on a coarse (grain) scale but not on a fine (martensitic plate) scale.
Real time nondestructive evaluation is required for composites load testing. The early detection and measurement of damage progression is important to understand failure modes. A single stringer panel was subjected to quasi-static loading to induce deformation which can result in the formation of delamination damage between the stiffener flange and skin. Passive thermography was used to detect damage in real time as a function of the applied load. The loading was stopped when damage growth was detected. Of particular interest was the early detection of damage formation which can be challenging, as compared to cyclic fatigue loading. Passive thermography data were acquired and processed in real time and revealed damaged areas due to heating from fiber breakage and delamination formation. The processed thermal imagery was also compared to acoustic emission and ultrasound data.
A series of experiments were conducted in an anechoic chamber to investigate the noise and performance of an ideally twisted rotor design, leading to validation of a low-fidelity aerodynamic performance and acoustic modeling tool chain. An "ideally twisted" rotor was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor design was then fabricated using state-of-the-art rapid prototyping and tested in an anechoic chamber facility. Aerodynamic load and acoustic data were acquired across a range of rotation rates (RPM) and rotor collective settings in order to ascertain the accuracy of the low-fidelity modeling codes. Emphasis was placed on modeling of the broadband self-noise generated by the rotor system due to the fact that it was found to be a prominent contributor to the overall rotor system noise.
A series of experiments were conducted in an anechoic chamber to investigate the noise and performance of an ideally twisted rotor design, leading to validation of a low-fidelity aerodynamic performance and acoustic modeling tool chain. An “ideally twisted” rotor was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor design was then fabricated using state-of-the-art rapid prototyping and tested in an anechoic chamber. Aerodynamic load and acoustic data were acquired across a range of rotation rates and rotor collective settings in order to both identify noise trends and ascertain the accuracy of the low-fidelity modeling codes. Emphasis was placed on modeling of the broadband self-noise generated by the rotor system due to the fact that it was found to be a prominent contributor to the overall rotor system noise.
The emergence of small Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) vehicles has motivated the need to acoustically characterize the rotors found on these vehicle platforms. Hover chamber tests of small rotors are beneficial in assessing the noise impact of UAS, and potentially larger AAM vehicles. Various experiments have been conducted in the NASA Langley Small Hover Anechoic Chamber (SHAC), formerly known as the Small Anechoic Jet Facility (SAJF), in order to investigate the noise and performance of small rotors. One of these tests was that of an “ideally twisted rotor”, which was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor was fabricated using state-of-the-art rapid prototyping and tested in the SHAC. Aerodynamic load and acoustic data were acquired across a range of rotation rates and rotor collective settings. Both tonal and broadband components were identified in the acoustic data, with broadband noise being a prominent contributor to the overall rotor system noise.
An effort to maximize memory bandwidth utilization for a sparse linear algebra kernel executing on NVIDIA® Tesla V100 and A100 Graphics Processing Units (GPUs) is described. The kernel consists of a block-sparse matrix-vector product and a series of forward/backward triangular solves. The computation is memory-bound and exhibits low arithmetic intensity. Along with a relatively small block size, the data layout poses a challenge to effectively utilize the available memory bandwidth on common GPU architectures. An earlier implementation using a warp to process a single row of the matrix was found to yield good memory performance on the V100 architecture. However, anew approach, which assigns a warp to six rows of the matrix, is proposed for the A100. In addition, two new features offered by the A100 architecture are explored.L2residency control enables a portion of theL2cache to be used for persistent data access, and the asynchronous copy instruction allows data to be loaded directly from main memory into shared memory. Demonstrations show that the new implementation improves memory bandwidth utilization from 71.5% to 81.2% of the peak available on theA100 architecture.
Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.
Workload has long been associated with human performance in aviation. High workload is typically viewed as a system design problem. The aim of this work was to find observable behaviors that guard cognitive resource margins; thus, improve handling of perturbations that arise. Twelve commercial airline flight crews participated in an experiment at NASA Langley Research Center. We explored workload data (NASA Task Load Index) self-reported after completing flight simulation scenarios to see how different individuals, using the same technologies, cope with challenging situations. A trained observer from the same airline as the study participants assessed performance. We differentiated a lower workload crew from a higher workload crew and analyzed their workload and performance. Results indicate that the workload may be a component of pilots’ resilient performance. Initial strategies that reduced workload were classified and these types of behaviors, if implemented correctly, might assist pilots in maintaining functional workload resource margins.
The NASA Glenn Research Center’s Power Architecture and Analysis Branch performs spacecraft electrical power system (EPS) performance analysis using the System Power Analysis for Capability Evaluation (SPACE) model. Accurately predicting EPS performance requires a wide range of inputs, including the spacecraft’s position, attitude, solar array temperature, load demand, and data on the EPS itself. By operating as a combined analysis tool with integrated orbit mechanics, attitude, shadowing, thermal, solar array, battery, and electrical component models, SPACE provides flexibility for the analyst to examine various scenarios without a time-consuming iterative process involving separate analysis tools and groups. SPACE also achieves short run times by tailoring the complexity of the included models, providing enough fidelity to ensure accurate EPS performance predictions without being bogged down by unnecessary detail. These advantages that SPACE has over similar power system models has contributed to its successful use on a variety of human spaceflight programs for over three decades, and makes it applicable across the development cycle from early conceptual design up through on-orbit operations.
Safe use of high energy density batteries is critical for electrifying aerospace and other transportation sectors. Nondestructive evaluation (NDE) techniques are being developed for characterizing battery structures throughout their lifetimes so that damage mechanisms can be better understood, and prognostic tools can be developed. In this study Local Ultrasonic Resonance Spectroscopy (LURS) is applied to lithium metal pouch cell batteries of a variety of form-factors that are brought from fabrication to end of life under different charge rates, temperatures, and loading scenarios. LURS data shows improved sensitivity to changes in structure in comparison to amplitude-based methods, allowing differences in damage development to be identified as well as giving opportunities for quality control in manufacturing.
Safe use of high energy density batteries is critical for electrifying aerospace and other transportation sectors. Nondestructive evaluation (NDE) techniques are being developed for characterizing battery structures throughout their lifetimes so that damage mechanisms can be better understood, and prognostic tools can be developed. In this study Local Ultrasonic Resonance Spectroscopy (LURS) is applied to lithium metal pouch cell batteries of a variety of form-factors that are brought from fabrication to end of life under different charge rates, temperatures, and loading scenarios. LURS data shows improved sensitivity to changes in structure in comparison to amplitude-based methods, allowing differences in damage development to be identified as well as giving opportunities for quality control in manufacturing.
Composite materials have become a popular choice in aerospace engineering applications due to their low weight, high specific stiffness, high specific energy absorption, and economic synthesis. As use of composite materials has proliferated, the need for accurate simulation under extreme loading conditions is of increasing importance. *MAT_213 is a tabulated plasticity and damage material model in LS-DYNA designed for such use cases. To account for the nonlinear material response, a plasticity algorithm is used, which employs a non-associative flow rule with coefficients requiring experimental calibration. This work outlines an experimental methodology for calibrating these coefficients using the macroscopic stress-strain response and microscopic in-plane strain measurements from coupon scale experiments. The model material used for the development and demonstration of this methodology is a plain weave woven fabric with T300 carbon fiber tows in the warp direction and Kevlar© 49 fiber tows in the weft direction, and an Epon© 828/Epikure© 3223 thermoset epoxy matrix. Coupon-scale tensile testing performed at multiple fiber angles (carbon fibers oriented 0º, 22.5º, 45º, 67.5º, and 90º relative to the loading axis) provides data for multiple calibration processes. The measured plastic strain increments in the principal material coordinate are used to set limits for ratios between flow rule coefficients. The identified ranges are used to bound the search for a set of coefficients, leading to convergence of different coupon responses in the effective stress – effective plastic strain space. Flow rule coefficients found by this methodology are then used as (i) input for LS-DYNA simulations of uniaxial tension coupon tests at varying fiber angles, and (ii) comparison of predicted values for the plastic Poisson’s ratio in global coordinates with the experimentally measured one for all off-axis orientations. These results are quantitatively and qualitatively compared to macroscopic stress-strain curves and experimental strain components. The conformity of the experimentally measured quantities with those derived from the simulations provide a means for assessing the quality of calibrated coefficients.
The advanced air mobility sector has progressed in recent years with electric vertical take-Off and landing vehicles at the forefront. In response, the NASA Advanced Air Mobility Project has initiated the Advanced Air Mobility National Campaign to partner with industry to progress this emerging market. This resulted in NASA’s Revolutionary Vertical Lift Technology project to participate to progress research efforts for software tool validation for these advanced air mobility vehicle configurations. Noise has been identified as one of the main obstacles to succeeding in this emerging market for community acceptance. To further understand electric vertical take-Off and landing vehicle noise, an isolated Joby Aviation S4 propeller was tested in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel to aid in providing high quality performance, loads, and acoustic data. Details of test hardware and setup are described with a focus on acoustics, which includes facility, test model, microphone locations, and data acquisition system details. Additionally, the data processing techniques and completed test matrix for acoustic points are provided. To aid in identifying potential acoustic reflections, an acoustic reflection test was performed prior to the start of the test and highlighted the presence of reflections at every microphone location. Acoustic results are provided for various flight regimes for sweeps of blade pitch, RPM, flow angle, and wind speed. These results show an optimum RPM for a specific thrust level for noise, and further reductions in RPM can increase noise levels. This dataset will be used to evaluate and improve computational tools.
The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.
The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.
Many in the scientific community, particularly in publicly funded research, are pushing to adhere to more accessible data standards to maximize the findability, accessibility, interoperability, and reusability (FAIR) of scientific data, especially with the growing prevalence of machine learning augmented research. Online FAIR data repositories, such as the Open Science Framework (OSF), help facilitate the adoption of these standards by providing frameworks for storage, access, search, APIs, and other features that create organized hubs of scientific data. However, the wider acceptance of such repositories is hindered by the lack of support of hierarchical data formats, such as Technical Data Management Streaming (TDMS) and Hierarchical Data Format 5 (HDF5), that many researchers rely on to organize their datasets. Various tools and strategies should be used to allow hierarchical data formats, FAIR data repositories, and scientific organizations to work more seamlessly together. A pilot project at Los Alamos National Laboratory (LANL) addresses the disconnect between them by integrating the OSF FAIR data repository with hierarchical data renderers, extending support for additional file types in their framework. The multifaceted interactive renderer displays a tree of metadata alongside a table and plot of the data channels in the file. This allows users to quickly and efficiently load large and complex data files directly in the OSF webapp. Users who are browsing files can quickly and intuitively see the files in the way they or their colleagues structured the hierarchical form and immediately grasp their contents. This solution helps bridge the gap between hierarchical data storage techniques and FAIR data repositories, making both of them more viable options for scientific institutions like LANL which have been put off by the lack of integration between them.
This paper proposes a learning-based building flexibility estimation and control framework to improve system economics and resilience. A data-driven building load flexibility model consisting of weather forecasting and estimating load consumption is proposed to quantify building heating, ventilation, and air conditioning (HVAC) load flexibility. A reinforcement learning-based microgrid controller is proposed to dispatch distributed generators, distributed energy resources, and build HVAC loads while taking flexibility information as one of the inputs. Simulation analysis is conducted on the model of a real microgrid in California. The effectiveness of the proposed learning-based building flexibility estimation and control in reducing microgrid energy costs and improving the sustainability of critical loads is demonstrated.