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Tests from the Sierra Structural Dynamics verification test suite are reviewed. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.
An area that shows promise in enhancing structural integrity of aircraft and aerospace structures is the integrally stitched composite technology. The most recent generation of this technology is the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept developed by Boeing Research and Technology and the National Aeronautics and Space Administration. A joint test program on the assessment of damage containment capabilities of the PRSEUS concept for curved fuselage structures was conducted recently at the Federal Aviation Administration William J. Hughes Technical Center. The panel was subjected to axial tension, internal pressure, and combined axial tension and internal pressure load conditions up to fracture, with a through-the-thickness, two-bay notch severing the central stiffener. For the purpose of future progressive failure analysis development and verification, extensive post failure nondestructive and teardown inspections were conducted. Detailed inspections were performed directly ahead of the notch tip where stable damage progression was observed. These examinations showed: 1) extensive delaminations developed ahead of the notch tip, 2) the extent and location of damage, 3) the typical damage mechanisms observed in composites, and 4) the role of stitching and warp-knitting in the failure mechanisms. The objective of this paper is to provide a summary of results from these posttest inspections.
The Life Sciences Glovebox (LSG) is a rack-level payload facility designed to house biological investigations in a "workbench" type environment aboard the International Space Station (ISS). The facility is scheduled to be launched in September 2018 and will be installed in the Japanese Experiment Module (JEM) of the ISS. LSG is comprised of an extendable work volume, an airlock, an avionics package, a laptop, and supporting structure. The 450L work volume provides two levels of containment for investigations via the physical barrier of its structure and an internal, filtered airflow that results in a negative pressure relative to ISS cabin pressure. The facility provides many other resources for investigation use including 28 VDC power, 120 VAC power, heat rejection, data connections, and video. Portions of the interior surfaces of the work volume are ferrous, allowing investigations and supporting hardware to be magnetically affixed to these surfaces. A UV decontamination system and a variety of ancillary hardware are available for investigations to use while occupying LSG. An engineering unit on the ground is used for payload development and integrated verification testing. Once the facility is installed and commissioned, it will be managed by the same team that manages the Microgravity Science Glovebox (MSG), another rack-level payload facility that has been operating aboard the ISS since 2002. Experienced Investigation Payload Integration Managers (IPIMs), who also support MSG payloads, will be available to assist payload developers through the integration process. This presentation will provide an overview of the LSG facility and the planned investigation flow for the near future.
Over the past two decades there has been considerable effort by NASA Glenn and others to develop probabilistic codes to predict with reasonable engineering certainty the life and reliability of critical components in rotating machinery and, more specifically, in the rotating sections of airbreathing and rocket engines. These codes have, to a very limited extent, been verified with relatively small bench rig type specimens under uniaxial loading. Because of the small and very narrow database the acceptance of these codes within the aerospace community has been limited. An alternate approach to generating statistically significant data under complex loading and environments simulating aircraft and rocket engine conditions is to obtain, catalog and statistically analyze actual field data. End users of the engines, such as commercial airlines and the military, record and store operational and maintenance information. This presentation describes a cooperative program between the NASA GRC, United Airlines, USAF Wright Laboratory, U.S. Army Research Laboratory and Australian Aeronautical & Maritime Research Laboratory to obtain and analyze these airline data for selected components such as blades, disks and combustors. These airline data will be used to benchmark and compare existing life prediction codes.
The SAIC has the responsibility for independent test and validation of the SSE. They have been using a mathematical functions library package implemented in Ada to test the SSE IV and V process. The library package consists of elementary mathematical functions and is both machine and accuracy independent. The SSE Ada components evaluation includes code complexity metrics based on Halstead's software science metrics and McCabe's measure of cyclomatic complexity. Halstead's metrics are based on the number of operators and operands on a logical unit of code and are compiled from the number of distinct operators, distinct operands, and total number of occurrences of operators and operands. These metrics give an indication of the physical size of a program in terms of operators and operands and are used diagnostically to point to potential problems. McCabe's Cyclomatic Complexity Metrics (CCM) are compiled from flow charts transformed to equivalent directed graphs. The CCM is a measure of the total number of linearly independent paths through the code's control structure. These metrics were computed for the Ada mathematical functions library using Software Automated Verification and Validation (SAVVAS), the SSE IV and V tool. A table with selected results was shown, indicating that most of these routines are of good quality. Thresholds for the Halstead measures indicate poor quality if the length metric exceeds 260 or difficulty is greater than 190. The McCabe CCM indicated a high quality of software products.
Ionospheric plasma interaction effects on the International Space Station are discussed in the following paper. The large structure and high voltage arrays of the ISS represent a complex system interacting with LEO plasma. Discharge current measurements made by the Plasma Contactor Units and potential measurements made by the Floating Potential Probe delineate charging and magnetic induction effects on the ISS. Based on theoretical and physical understanding of the interaction phenomena, a model of ISS plasma interaction has been developed. The model includes magnetic induction effects, interaction of the high voltage solar arrays with ionospheric plasma, and accounts for other conductive areas on the ISS. Based on these phenomena, the Plasma Interaction Model has been developed. Limited verification of the model has been performed by comparison of Floating Potential Probe measurement data to simulations. The ISS plasma interaction model will be further tested and verified as measurements from the Floating Potential Measurement Unit become available, and construction of the ISS continues.
We studied the flow field characteristics of a turbulent flow over a regularized cube array with a perpendicular injection flow through the floor between the second and third cubical elements, representing the complex flow interactions of a 3D jet and the wake flows behind cubical obstacles. Four different experimental measurements were performed: two magnetic resonance imaging-based measurements for three-dimensional three-component velocity (MRV) and concentration (MRC) and two laser-based techniques, particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), for two-dimensional two-component velocity and concentration measurement, respectively. The mainstream Reynolds number is Re = 15 000, based on the primary inlet velocity U m and channel height D H , whereas the injector Reynolds number is Re j = 3400, based on the injector velocity U j and the injector's exit width D j . Numerical simulations were performed for the studied flow configuration of turbulent flow over a regularized cube array using Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulation (LES) approaches. Results obtained from experimental measurements—including MRV, MRC, PIV, and PLIF—as well as RANS and LES simulations are discussed and compared along several horizontal and vertical planes of the studied configuration. In addition, 3D turbulent flow structures, such as leading-edge vortex, horseshoe vortex, and jet shear-layer vortex, and the isosurfaces of scalar concentration successfully revealed by MRV and MRC techniques were found to be in very good agreement with those 3D features extracted from RANS and LES simulations. In conclusion, the high-resolution experimental and numerical database obtained from this study could be useful for validation and verification of numerical codes.
Crystals with complicated geometry are often observed with mixed chemical occupancy among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar systems possessing exact occupancy on all the sites can exhibit superstructural ordering, dramatically inflating the unit cell size. In this work, a crystal graph convolutional neural network (CGCNN) is used to predict optimal atomic decorations on fixed crystalline geometries. This is achieved with a site permutation search (SPS) optimization algorithm based on Monte Carlo moves combined with simulated annealing and basin-hopping techniques. Our approach relies on the evidence that, for a given chemical composition, a CGCNN estimates the correct energetic ordering of different atomic decorations, as predicted by electronic structure calculations. This provides a suitable energy landscape that can be optimized according to site occupation, allowing the prediction of chemical decoration in crystals exhibiting mixed or disordered occupancy, or superstructural ordering. Verification of the procedure is carried out on several known compounds, including the superstructurally ordered clathrate compound Rb8Ga27Sb16 and vacancy-ordered perovskite Cs2SnI6, neither of which was previously seen during the neural network training. In addition, the critical temperature of an order–disorder phase transition in solid solution CuZn is probed with our SPS routines by sampling site configuration trajectories in the canonical ensemble. This strategy provides an accurate method for determining favorable decoration in complex crystals and analyzing site occupation at unprecedented speed and scale.
Accurate mapping of forest aboveground biomass density (AGBD) is required to better understand the role of forests in the global carbon cycle and to support international policies for climate change mitigation and adaptation. Mexico is one of the countries having great potential for the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (or UN-REDD program) and there is a growing demand for unbiased Monitoring Reporting Verification systems at a national level. As an effort under NASA’s Carbon Monitoring System (CMS) program, we developed a machine learning model using multi-stream remote sensing measurements as well as topographic data to create a high spatial resolution AGBD map (~100 m) over Mexico (circa 2020). The remote sensing data includes Global Ecosystem Dynamic Investigation (GEDI) lidar, Sentinel 1 Synthetic-Aperture Radar (SAR), and Sentinel-2 multispectral imagery (MSI). GEDI onboard the International Space Station provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. Our analysis indicates that the developed random forest model can capture 63 % of the spatial variation (RMSE = 33.7 Mg/ha) of AGBD of Mexican forests. We find that shortwave infrared bands of Sentinel-2 MSI and topographical variables from elevation data are the most important variables in the developed AGBD model. Our study highlights methodological opportunities in synergistic uses of multiple sensors for large-scale forest AGBD mapping and shows potential for retrospective analysis and operational monitoring of forest AGBD and its dynamics.
This project advanced the development of an active hybrid mooring system integrating experimental testing with numerical simulation to capture complex mooring dynamics not feasible in existing wave basins, including deep-water and shared mooring interactions. Verification testing of the complete hybrid system yielded good agreement in mooring tension and platform translation responses, though discrepancies in platform pitch response indicate that further refinement may be needed in future work.
The United States Air Force has published a document entitled Aircraft Structural Integrity Program. One phase of the program is concerned with the fatigue life certification of all types of military aircraft. The document describes the criteria, analyses, and tests that are necessary in order to satisfy the USAF fatigue life requirement. Some recent and valid criticism has been directed toward the document, particularly the fatigue-life requirements contained in it. Some changes are proposed based on surveys conducted in the United States and abroad as well as some recent systems' experience. The surveys covered both military and civilian organizations. The fatigue certification case histories of selected military and commercial aircraft are presented. The design development element tests, preproduction design verification tests, and full-scale fatigue tests of each are described. A brief status report on the revisions to the MIL-A-008860 series specifications is included.
The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. New features in the 2.2 release include: DiagnosticsToolbox DiagnosticsToolbox (idaes.core.util.model_diagnostics. DiagnosticsToolbox is a new self-guiding toolbox for assisting with diagnosing modeling issues. The toolbox contains a wide range of tools for identifying common modeling issues and conveying these to the user, and more features will be added in the coming months. To try the new toolbox, use the following steps: from idaes.core.util import DiagnosticsToolbox Build an instance of your model Ensure your models has zero degrees of freedom (as best you can) dt = DiagnosticsToolbox(model) dt.report_structural_issues() Follow the prompts Deprecations DegeneracyHunter is being deprecated in favor of the new DiagnosticsToolbox. The features and capabilities of DegeneracyHunter will be moved over to the DiagnositcsToolbox in the coming months. Removal of usage of Pyomo's expr.current due to deprecation upstream. Removed support for radial basis functions in ALAMOpy as these did not work in the current implementation. Those wishing to use radial basis functions should use Pysmo instead. New Capabilities MSContactor model for unit operations involving mass transfer between 2 or more streams, such as membrane, solvent extraction and solids leaching operations. Other Improvements Improved formulation for solubility products with additional parameters for better scaling of terms Better backward compatibility, verification and robustness testing of core models and APIs Added support for Separator models without energy balances
Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.
The Orion Multi-Purpose Crew Vehicle program was performing a proof pressure test on an engineering development unit (EDU) of the Orion Crew Module Side Hatch (CMSH) assembly. The purpose of the proof test was to demonstrate structural capability, with margin, at 1.5 times the maximum design pressure, before integrating the CMSH to the Orion Crew Module structural test article for subsequent pressure testing. The pressure test was performed at lower pressures of 3 psig, 10 psig and 15.75 psig with no apparent abnormal behavior or leaking. During pressurization to proof pressure of 23.32 psig, a loud 'pop' was heard at ~21.3 psig. Upon review into the test cell, it was noted that the hatch had prematurely separated from the proof test fixture, thus immediately ending the test. The proof pressure test was expected be a simple verification but has since evolved into a significant joint failure investigation from both Lockheed Martin and NASA.
The Third Wind Forecast Improvement Project (WFIP3) is a multi-institutional field campaign designed to advance the understanding and prediction of the offshore atmospheric boundary layer along the US east coast. Extending from February 2024 through August 2025, WFIP3 combines long-term coastal and offshore measurements with targeted modeling and forecasting efforts. This data paper presents the WFIP3 event log, a curated record of 578 d of meteorological phenomena and field observations that complements the campaign's extensive high-frequency datasets. The event log provides both manually documented daily weather discussions and automatically derived indicators of atmospheric processes – including low-level jets, wind ramps, extreme wind veer, and weak wind conditions – based on observations from scanning lidars deployed at three coastal and offshore sites. The dataset offers structured metadata, standardized time and site identifiers, and consistent terminology to facilitate its integration with WFIP3's observational and modeling data products. The log supports diverse applications, from model evaluation and forecast verification to the selection of case studies on offshore boundary-layer dynamics. The WFIP3 event log is publicly available through the US Department of Energy's Wind Data Hub, providing the research community with a transparent and enduring contextual reference for the interpretation and use of WFIP3 measurements.
This paper presents results from Phase II of the OC7 project, focusing on hydroelastic modeling and member-level load prediction for a flexible floating offshore structure. Numerical predictions from 11 academic and industrial partners are validated against experimental measurements obtained from a 1:70-scale test of the VolturnUS-S semisubmersible platform. A comprehensive set of verification and validation cases is examined. The results demonstrate that hydrodynamic added mass has a significant impact on predicted elastic natural frequencies. Under regular wave excitation, the numerical models reproduce platform motions and mooring line tensions with good accuracy. Member-level loads are also predicted with reasonable accuracy. Some discrepancies are observed for potential-flow models not accounting for higher-order effects associated with the instantaneous wetted surface.
Two-stage anaerobic digestion (AD) systems provide treatment for high strength wastewater with high stability and performance. Encapsulation technology can intensify AD to facilitate the separation of the solids retention time from the hydraulic retention time (HRT), offering lower HRTs, smaller reactors, and high effluent quality. To support successful deployment, however, the encapsulated community must contain all the needed microorganisms for successful treatment and be flexible enough to treat a variety of wastewaters. Here, a two-stage system was investigated in which microbial cultures were enriched on various high-strength wastewaters in suspended flow-through systems to determine how feed type influenced performance and microbial community structure. The hypothesis was that specific genera, or so-called “keystone species” would positively correlate to organic carbon degradation for a given feed, enabling construction of a well-functioning community for encapsulation. Results showed that the number of total bacteria (as 16S rRNA gene copies) did not correlate to soluble chemical oxygen demand (sCOD) removal, indicating that the community structure and/or members were important for good performance. Results also showed that feed type strongly influenced carbon removal and microbial community structure for 1st-stage fermenting communities, but not 2nd-stage methanogenic communities. In this study, the “core” community members were defined as organisms common to all of either the 1st- or 2nd-stage reactors irrespective of the feed they received and were present in at least 50% of the samples throughout the entire experiment. “Unique” community members were specific to a single feed, and hence, only present in either the 1st- or 2nd-stage reactors receiving that feed. In both 1st- and 2nd-stage communities, only one core genera and no unique genera were positively and significantly correlated to sCOD removal. Verification experiments performed with encapsulated communities showed that organisms identified in flow-through system and correlated with carbon degradation, though not significantly, seemed to be important for performance. Our results suggest that one cannot construct a community containing specific populations in lieu of enrichment. Nevertheless, a single diverse encapsulated anaerobic community should provide good (>80%) carbon removal when fed a variety of influents, if time is provided for enrichment after deployment.
This paper presents both near-term and long-term NASA Advanced Extra-vehicular Activity (EVA) Pressure Garment development efforts. The near-term plan discusses the development of pressure garment components for the first design iteration of the International Space Station exploration space suit demonstration configuration, termed the xEMU Demo. The xEMU Demo effort is targeting a 2023-2025 flight demonstration timeframe. The Fiscal Year 2018 (FY18) tasks focus on either the initiation or maturation of component design, depending on the state of development of the components, and the assembly of a suit configuration, termed Z-2.5, that will be used to evaluate changes to the upper torso geometry in a Neutral Buoyancy Laboratory (NBL) test series. The geometry changes, which are being driven by the need to reduce the front-to-back dimension of the advanced extravehicular mobility unit, diverge from a proven shape, such as that of the Mark III Space Suit Technology Demonstrator. The 2018 efforts culminate in the Z-2.5 NBL test. The lessons learned from the Z-2.5 NBL test will inform the xEMU Demo design as the effort moves toward design verification testing and preliminary and critical design reviews. The long-term development plan looks to surface exploration and operations. Technology and knowledge gaps exist between the xEMU Demo configuration; a lunar surface capability, xEMU; and Mars surface suit, mEMU. The development plan takes into account both the priority and the anticipated development duration for each particular technology. The long-term development plan will be updated as risks are mitigated and gaps are closed, but its overarching structure will remain intact.