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The paper presents and compares two approaches to design fault-tolerant evolvable hardware: one based on the fitness definition and the other based on the population statistics.
In this paper, an approach is described, which involves the fit of a combination of two simple scattering mechanisms to polarimetric SAR observations.
This Technical Memorandum presents results from a damage tolerance study undertaken in support of the payload adapter fitting (PAF) for the Space Launch System (SLS) program at NASA’s Marshall Space Flight Center (MSFC). The study consisted of determining the compression-after-impact (CAI) strength of candidate carbon/epoxy face sheet sandwich structure that has been identified for potential use to manufacture the PAF hardware. Two types of core material that have been considered for use on the PAF structure were used in this study. One was an aluminum honeycomb and the other was a Rohacell foam. Levels of barely visible impact damage (BVID) were determined for the types of sandwich structure tested in this study and this level of damage was used for CAI strength testing. It was found that the honeycomb core sandwich structure failed by face sheet failure and the foam core sandwich structure failed by core shear failure. CAI strength values were normalized by weight of the sandwich structure since lower mass is desirable for this structure.
As technology evolves and improves within the science of composite materials, new fiber/ resin systems are being developed for improved properties given certain loading and environmental scenarios. Improving the room temperature damage tolerance capabilities has long been one of the goals in the carbon fiber/polymer composite industry. Recently a new fiber/epoxy system has been introduced that is claimed to have superior damage tolerance capabilities. To examine if this new carbon fiber/epoxy composite material would be of benefit to a program to manufacture a Payload Adapter Fitting (PAF) for NASA’s Space Launch System (SLS) rocket, the question was asked as to just how much damage tolerance could be realized if this new system were used. Compression after impact (CAI) strength of sandwich structure is one of the leading metrics being used to evaluate materials for the PAF program. As a result, a comparison of this new fiber/resin system with a very common (and planned baseline) fiber/resin system with respect to CAI was considered in this study. While it was already known that the older, baseline carbon fiber structure would not have as good damage tolerance characteristics as the newer carbon fiber system, the quantitative difference in damage tolerance was sought in this study since no other CAI data could be found in open literature on sandwich structures made with this new fiber/resin system.
With the increased emphasis on reducing the cost and time to market of new materials, ICME (Integrated Computational Materials Engineering) has become a fast growing discipline within materials science and engineering. The vision of ICME is compelling in many respects, not only for the value added in reducing time to market for new products with advanced, tailored materials, but also for enhanced efficiency and performance of these materials. Although the challenges and barriers (both technical and cultural) are formidable, substantial cost, schedule, and technical benefits can result from broad development, implementation, and validation of ICME principles. ICME is an integrated approach to the design of products, and the materials that comprise them, by linking material and structural models at multiple time and length scales. NASA’s Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) in 2016 to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review ICME, the findings of the 2040 Vision study, and discuss NASA’s TTT 2040 implementation activities: with special emphasis on recent accomplishments. The 2040 study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems by enabling the engineer to not only “design-with-the” material but also concurrently “design-the” material.
Nitrogen dioxide (NO 2 ) is an important trace-gas pollutant and climate agent whose presence also leads to spectral interference in ocean color retrievals. NO 2 column densities have been retrieved with satellite UV–Vis spectrometers such as the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI) that typically have spectral resolutions of the order of 0.5 nm or better and spatial footprints as small as 3.6 km × 5.6 km. These NO 2 observations are used to estimate emissions, monitor pollution trends, and study effects on human health. Here, we investigate whether it is possible to retrieve NO 2 amounts with lower-spectral-resolution hyperspectral imagers such as the Ocean Color Instrument (OCI) that will fly on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite set for launch in early 2024. OCI will have a spectral resolution of 5 nm and a spatial resolution of ∼ 1 km with global coverage in 1–2 d. At this spectral resolution, small-scale spectral structure from NO 2 absorption is still present. We use real spectra from the OMI to simulate OCI spectra that are in turn used to estimate NO 2 slant column densities (SCDs) with an artificial neural network (NN) trained on target OMI retrievals. While we obtain good results with no noise added to the OCI simulated spectra, we find that the expected instrumental noise substantially degrades the OCI NO 2 retrievals. Nevertheless, the NO 2 information from OCI may be of value for ocean color retrievals. OCI retrievals can also be temporally averaged over timescales of the order of months to reduce noise and provide higher-spatial-resolution maps that may be useful for downscaling lower-spatial-resolution data provided by instruments such as OMI and TROPOMI; this downscaling could potentially enable higher-resolution emissions estimates and be useful for other applications. In addition, we show that NNs that use coefficients of leading modes of a principal component analysis of radiance spectra as inputs appear to enable noise reduction in NO 2 retrievals. Once trained, NNs can also substantially speed up NO 2 spectral fitting algorithms as applied to OMI, TROPOMI, and similar instruments that are flying or will soon fly in geostationary orbit.
A payload adaptor fitting (PAF) has been manufactured at NASA’s Marshall Space Flight Center (MSFC) in support of the Space Launch System (SLS) program. This structure is essentially a large cone made up of eight curved “lobes” that are joined together to form the cone. The lobes were manufactured via automated fiber placement (AFP). The PAF will carry predominantly compressive loads thus compression strength will be the focus of this study. The lobes are sandwich structure made with aluminum honeycomb core and carbon/epoxy face sheets. The lobes will be inserted into metallic rings at the top and bottom of the cone to form the full cone. Both front and back exterior surfaces of each lobe have a plain weave fabric placed at ±45⁰ to the vertical direction to help prevent fiber “breakout” during drilling. The face sheet of each lobe is thickest at the top and plies are dropped as the cone reaches the main acreage in the bottom section of the cone. The entire structure used resin impregnated peel ply that, once removed, supplies a good bonding surface for secondary bonding steps. The peel ply can be removed either directly after cure, or just before any bonding operation. Since foreign object impact can occur to the structure at any time during its life, damage tolerance of the PAF structure both with and without peel ply needed to be addressed because a previous study, albeit with limited data, showed some significant differences in damage tolerance whether the peel ply was present or not [1]. A literature search showed no results for comparing impact damage on composite laminates with and without peel ply. Load versus deflection of impact curves, visual damage, dent depth, damage as ascertained by thermography and cross-sectional microscopy were evaluated as part of the damage resistance of the structure. Compression After Impact (CAI) was performed to assess damage tolerance. The impact tests were conducted on representative specimens both with and without the peel ply present.
With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.
Fitting Procedure for SOLR Oxygen mask by EC4 in collaboration with Airborne Systems
No abstract available
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
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For flexibility in forming a curved surface, a honeycomb configuration using multiple pleats has proved superior to the usual core structures. The partial pleats formed in individual cell walls permit movements to and from the central axis without tearing.
A simplified computer logic circuit of two NAND/NOR gates and three additional inputs to accomplish the count and shift function is described. The circuit has capacity for parallel read-in, counting, serial shiftout, complement input and set and reset.
Linear programming for approximate computation of guidance function for adaptive control systems