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Negative stress margins – are they real?
Advances in modeling and simulation, new finite element software, modeling engines and powerful computers are providing opportunities to interrogate designs in a very different manner and in a more detailed approach than ever before. Margins of safety are also often evaluated using local stresses for various design concepts and design parameters quickly once analysis models are defined and developed. This paper suggests that not all the negative margins of safety evaluated are real. The structural areas where negative margins are frequently encountered are often near stress concentrations, point loads and load discontinuities, near locations of stress singularities, in areas having large gradients but with insufficient mesh density, in areas with modeling issues and modeling errors, and in areas with connections and interfaces, in two-dimensional (2D) and three-dimensional (3D) transitions, bolts and bolt modeling, and boundary conditions. Now, more than ever, structural analysts need to examine and interrogate their analysis results and perform basic sanity checks to determine if these negative margins are real.
Event Report for The Ethical Artificial Intelligence Quantification Workshop
Artificial Intelligence (AI) is a powerful emerging technology area which requires special attention to using it ethically. AI ethics is still an emerging field, and the partners for this workshop and report seek to move AI ethics discussion ahead by experimenting with ways to measure AI ethics criteria. The following document describes the outcomes and learnings from The Ethical Artificial Intelligence Quantification Workshop held at the National Institute for Aerospace (NIA), Hampton, Virginia on May 12th, 2022. The purpose of the workshop was for participants to evaluate and experiment-with the methodology and process presented by AIEthics.World in cooperation with Intel Corporation. The meeting participants learned about the Ethical AI Certification and Maturity Model™ and applied the methodology to selected notional AI systems. The workshop facilitated the evaluation of the maturity of the AI system according to ethical considerations relevant to NASA, NIA and other participants. The workshop consisted of three main phases. The first phase focused on understanding and summarizing NASA’s ethical approaches, mission and values based on published documentation, discussions and individual insights & opinions of participants. This information was prioritized, weighted, ordered, and quantified in phase two, to formulate an alignment between human values (ethics) and their applicability to AI systems during all lifecycle phases. The first two phases were summarized as a form of ethical genealogy for artificial intelligence, specific to NASA’s ethical approaches. In the third and last phase of the workshop the participants evaluated notional examples of artificial intelligence to qualify and quantify its ability to adhere to the organizational ethics approaches, using the Ethical AI Certification and Maturity Model™. The workshop uses the concept of genealogy, in the traditional sense: the study and traceability of lines of ancestors in the process of evolutionary development from earlier forms. However, as it is applied to an Ethical AI definition, it is providing the insights to the necessary and mandatory traceability of content, data, metrics, telemetry, elements, and structures which are used in the AI’s lifecycle to foster and measure AI ethics in all steps of its lifecycle. The Ethical Artificial Intelligence Quantification Workshop provided NASA with the opportunity to apply the Ethical AI Certification and Maturity Model™, in combination with existing and well-known decision-making and quality control methods to identify the metrics and measurements for an Ethical AI and assess its ethical condition and quality aligned with NASA ethics approaches. The result of the workshop is the capacity for NASA to apply the maturity model assessment to its AI Systems as desired and if necessary, publish the ability of these AI Systems to adhere to the organizational ethical goals. AI ethics frameworks need to be customized for each application domain, for example, individual NASA Mission Directorates. General principles that work in one area such as AI/Machine Learning-based text analysis (the ethics of information-extraction) may need to be adapted for another such as sense-and-avoid decision-making in a flight environment. The workshop was conducted among approximately twenty NASA subject matter experts, so the elements noted above should be considered examples, not definitive NASA ethical AI principles, genealogy, etc. Generating a definitive AI ethics framework for an organization as diverse as NASA would require far more discussion, debate, review, etc. However, the workshop provided valuable insight into mechanisms and processes for quantifying AI ethical qualities.
Development of the METMAN Thermal Desktop Human Model for System Integration
Human thermal analysis and model development inform NASA’s space suit development, vehicle/habitat design, and survivability studies. Historically, human thermal models such as the 41-node metabolic man (METMAN) and the Wissler model have been standalone software tools developed with FORTRAN, a programming language known for its high performance in computationally intensive applications. Though efficient, these standalone programs pose challenges to coupled human-system analysis with detailed life support and thermal control subsystem models in other commercial software. This paper describes the conversion of the METMAN human thermal model from a standalone FORTRAN program to a model in Thermal Desktop (Ansys), a commonly used CAD-based simulation software for engineering that specializes in heat transfer, thermal radiation, and fluid flow analysis. This format was chosen to best facilitate model sharing and compatibility, enabling the direct integration of METMAN human thermal analysis with subsystem models across NASA programs and commercial partners.
SOWFA Super-Controller: A High-Fidelity Tool for Evaluating Wind Plant Control Approaches
This paper presents a new tool for testing wind plant controllers in the Simulator for Offshore Wind Farm Applications (SOWFA). SOWFA is a high-fidelity simulator for the interaction between wind turbine dynamics and the fluid flow in a wind plant. The new super-controller testing environment in SOWFA allows for the implementation of the majority of the wind plant control strategies proposed in the literature.
Residential Multi-Function Gas Heat Pump
This fact sheet describes a project by Southwest Gas Corporation, in collaboration with IntelliChoice Energy and Oak Ridge National Laboratory, to develop hardware and software for engine and system controls for a residential gas heat pump system that provides space cooling, heating, and hot water.
From PeleC to PeleACC, to PeleC++
PeleC is an Exascale Computing Project application for simulating compressible combustion in complex geometries. It has been built on top of the popular AMReX library. In the beginning of the Exascale Computing Project, PeleC was focused on KNL. It uses a mixture of C++, C, and kernels written in Fortran to obtain performance by focusing on vectorization. Recently we have taken two approaches in deciding PeleC's future for obtaining performance on exascale GPU machines. In the first programming model, we decorated the Fortran kernels with OpenACC directives. This expedited our ability to run at large scales on Summit's GPUs, where we achieved a significant speedup over the CPUs on Summit. The second programming model involved rewriting the Fortran kernels in C++ and using AMReX's Kokkos-like lambda abstractions for running on the GPU. This resulted in similar speedups on Summit's GPUs over merely utilizing the CPUs. Both approaches involved AMReX's management of memory transfers between the device and host. In this work, we compare and contrast the benefits and pitfalls to both programming approaches regarding performance, performance portability, and productivity. We also discuss advantages we have found in taking the time to modernize our code and why have chosen a specific pathway to prepare our code for the future DOE exascale machines.
BIM Interoperability Tool for Improving IFC-based Model Data Exchange Between Architectural Design and Structural Analysis for Linear Piping Components
There is a growing need in the AEC industry for the digitalization of model-based data exchange in BIM workflows. However, users continue to face difficulties exchanging data between BIM-based computer-aided design (CAD) and computer-aided engineering (CAE) software, even with the open, non-proprietary data exchange format called Industry Foundation Classes (IFC). Proposed solutions in academic research focus primarily on building systems, with comparatively little attention to piping models. Therefore, this paper introduces an interoperability tool for enabling piping model data exchange between architectural and structural analysis domains. The tool is tested using a piping model created in Autodesk Revit and shows marked improvement for IFC-based CAD-to-CAE interoperability over existing practice.
Firing Room Remote Application Software Development
The Engineering and Technology Directorate (NE) at National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) is designing a new command and control system for the checkout and launch of Space Launch System (SLS) and future rockets. The purposes of the semester long internship as a remote application software developer include the design, development, integration, and verification of the software and hardware in the firing rooms, in particular with the Mobile Launcher (ML) Launch Accessories (LACC) subsystem. In addition, a software test verification procedure document was created to verify and checkout LACC software for Launch Equipment Test Facility (LETF) testing.
Operating executive for the DSIF tracking subsystem software
The advanced engineering model of the DSIF tracking subsystem (DTS) is being developed by the Deep Space Instrumentation Facility. The DTS will provide effective and reliable tracking and data acquisition support for the complex planetary and interplanetary space flight missions planned for the 1970's. The nucleus of the subsystem is a Honeywell H832 digital computer. The design and capabilities of the real-time operating executive software are described.
Enhancement/upgrade of Engine Structures Technology Best Estimator (EST/BEST) Software System
This report describes the work performed during the contract period and the capabilities included in the EST/BEST software system. The developed EST/BEST software system includes the integrated NESSUS, IPACS, COBSTRAN, and ALCCA computer codes required to perform the engine cycle mission and component structural analysis. Also, the interactive input generator for NESSUS, IPACS, and COBSTRAN computer codes have been developed and integrated with the EST/BEST software system. The input generator allows the user to create input from scratch as well as edit existing input files interactively. Since it has been integrated with the EST/BEST software system, it enables the user to modify EST/BEST generated files and perform the analysis to evaluate the benefits. Appendix A gives details of how to use the newly added features in the EST/BEST software system.
Parameter Estimator for Engineering Systems
This software model generates vehicle parameter sets for downstream modeling applications using real-world data. Value to users is provided through improvements to modeling activities as a result of decreases in time taken during model development and validation. Currently configured for transportation modeling activities, the software provides initial estimates for multiple fundamental vehicle parameters including mass, coefficient of drag, and tire rolling resistance using real-world drive and duty cycle information as inputs.
Software For Computer-Aided Design Of Control Systems
Computer Aided Engineering System (CAESY) software developed to provide means to evaluate methods for dealing with users' needs in computer-aided design of control systems. Interpreter program for performing engineering calculations. Incorporates features of both Ada and MATLAB. Designed to be flexible and powerful. Includes internally defined functions, procedures and provides for definition of functions and procedures by user. Written in C language.
F100 Multivariable Control Synthesis Program. Computer Implementation of the F100 Multivariable Control Algorithm
As turbofan engines become more complex, the development of controls necessitate the use of multivariable control techniques. A control developed for the F100-PW-100(3) turbofan engine by using linear quadratic regulator theory and other modern multivariable control synthesis techniques is described. The assembly language implementation of this control on an SEL 810B minicomputer is described. This implementation was then evaluated by using a real-time hybrid simulation of the engine. The control software was modified to run with a real engine. These modifications, in the form of sensor and actuator failure checks and control executive sequencing, are discussed. Finally recommendations for control software implementations are presented.
Identification and interpretation of patterns in rocket engine data
A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.
Impeller leakage flow modeling for mechanical vibration control
HPOTP and HPFTP vibration test results have exhibited transient and steady characteristics which may be due to impeller leakage path (ILP) related forces. For example, an axial shift in the rotor could suddenly change the ILP clearances and lengths yielding dynamic coefficient and subsequent vibration changes. ILP models are more complicated than conventional-single component-annular seal models due to their radial flow component (coriolis and centrifugal acceleration), complex geometry (axial/radial clearance coupling), internal boundary (transition) flow conditions between mechanical components along the ILP and longer length, requiring moment as well as force coefficients. Flow coupling between mechanical components results from mass and energy conservation applied at their interfaces. Typical components along the ILP include an inlet seal, curved shroud, and an exit seal, which may be a stepped labyrinth type. Von Pragenau (MSFC) has modeled labyrinth seals as a series of plain annular seals for leakage and dynamic coefficient prediction. These multi-tooth components increase the total number of 'flow coupled' components in the ILP. Childs developed an analysis for an ILP consisting of a single, constant clearance shroud with an exit seal represented by a lumped flow-loss coefficient. This same geometry was later extended to include compressible flow. The objective of the current work is to: supply ILP leakage-force impedance-dynamic coefficient modeling software to MSFC engineers, base on incompressible/compressible bulk flow theory; design the software to model a generic geometry ILP described by a series of components lying along an arbitrarily directed path; validate the software by comparison to available test data, CFD and bulk models; and develop a hybrid CFD-bulk flow model of an ILP to improve modeling accuracy within practical run time constraints.
NASA Data Acquisition System Software Development for Rocket Propulsion Test Facilities
Current NASA propulsion test facilities include Stennis Space Center in Mississippi, Marshall Space Flight Center in Alabama, Plum Brook Station in Ohio, and White Sands Test Facility in New Mexico. Within and across these centers, a diverse set of data acquisition systems exist with different hardware and software platforms. The NASA Data Acquisition System (NDAS) is a software suite designed to operate and control many critical aspects of rocket engine testing. The software suite combines real-time data visualization, data recording to a variety formats, short-term and long-term acquisition system calibration capabilities, test stand configuration control, and a variety of data post-processing capabilities. Additionally, data stream conversion functions exist to translate test facility data streams to and from downstream systems, including engine customer systems. The primary design goals for NDAS are flexibility, extensibility, and modularity. Providing a common user interface for a variety of hardware platforms helps drive consistency and error reduction during testing. In addition, with an understanding that test facilities have different requirements and setups, the software is designed to be modular. One engine program may require real-time displays and data recording; others may require more complex data stream conversion, measurement filtering, or test stand configuration management. The NDAS suite allows test facilities to choose which components to use based on their specific needs. The NDAS code is primarily written in LabVIEW, a graphical, data-flow driven language. Although LabVIEW is a general-purpose programming language; large-scale software development in the language is relatively rare compared to more commonly used languages. The NDAS software suite also makes extensive use of a new, advanced development framework called the Actor Framework. The Actor Framework provides a level of code reuse and extensibility that has previously been difficult to achieve using LabVIEW. The