Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “knowledge engineering”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Morris, Robert A.↗

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 28: The technical communication practices of aerospace engineering and science students: Results of the phase 4 cross-national surveys

This report describes similarities and differences between undergraduate and graduate aerospace engineering and science students in the context of two general aspects of the educational experience. First, we explore the extent to which students differ regarding the factors that lead to the choice of becoming an aerospace engineer or a scientist, current satisfaction with that choice, and career-related goals and objectives. Second, we look at the technical communication skills, practices, habits, and training of aerospace engineering and science students. The reported data were obtained from a survey of students enrolled in aerospace engineering and science programs at universities in India, Japan, Russia, and the United Kingdom. The surveys were undertaken as part of the NASA/DOD Aerospace Knowledge Diffusion Research Project. Data are reported for the following categories: student demographics; skill importance, skill training, and skill helpfulness; collaborative writing; computer and information technology use and importance, use of electronic networks; use and importance of libraries and library services; use and importance of information sources and products; use of foreign language technical reports; and foreign language (reading and speaking) skills.

Pinelli, Thomas E.↗

A method for diagnosing time dependent faults using model-based reasoning systems

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Goodrich, Charles H.↗

KATE: From the lab to the firing room

For the past 9 years, the AI group at NASA's Kennedy Space Center (KSC) has been developing a real-time model-based reasoning (MBR) system that can diagnose faults and provide control advisories. The system resulting from this effort is called KATE (Knowledge-based Autonomous Test Engineer). This article describes the transition of KATE from the applied research lab to the firing room (the firing room is the main control and monitoring center for all Shuttle ground support and launch processing). Because the problems that were countered along the way are not unique, we decided to share some of our experiences. This article also includes a brief overview of the latest application of KATE.

Pepe, Charles↗

Superior Ballistic Impact Resistance Achieved by the Co-Base Alloy Haynes 25

The fan case in a jet engine is required to contain a fan blade in the rare event of a blade loss during operation. Because of its function, the fan case is the largest structural component in high-bypass-ratio turbofan engines used in commercial aircraft. Therefore, the use of lighter and stronger materials would be advantageous in most engines and is practically a necessity in the latest generation of high-bypass engines. Small panels, 7 in. wide by 7 in. long, of a number of metallic alloys were impact tested at room temperature with a 0.50-caliber blunt-nose titanium alloy projectile at the NASA Glenn Research Center (ref. 1). These metallic systems included several high-strength aluminum (Al) alloys, Al-based laminates, aluminum metal matrix composites (Al-MMCs), nickel-base superalloys (Inconel 718 and 625), several titanium (Ti) alloys in different heat treated conditions, 304L stainless steel, a stainless-steel-based laminate, and a high strength steel (Nitronic 60). It was determined that a simple Co-base alloy (Haynes 25) had the best impact resistance on an areal weight basis. Haynes 25 was at least 10 percent better than IMI 550, the best titanium alloy tested to date, and it was far superior to other metals, especially at higher impact velocities (greater than 1100 ft/sec). Because this material could be ideal for fan containment applications in supersonic aircraft as a replacement for titanium, impact tests were also conducted at 371 oC and compared with results from alloys tested at elevated temperature under previous programs (i.e., Inconel 718, Ti-6242, M-152, Timetal 21S, and Aeromet 100). Although cobalt-base alloys are used in some high-temperature engine applications, to our knowledge they are not used in any containment systems. Advantages of cobalt over titanium include lower cost, easier processing, better high-temperature strength, and no fire hazard if tip rub occurs. Future plans include testing of lightweight sandwich panels with Haynes 25 as a core material in the form of a foam or lattice block structure and scaling up the current tests by using blade-simulating projectiles impacting large plates and half rings.

Hebsur, Mohan G.↗

Large Engine Technology (LET) Short Haul Civil Tiltrotor Contingency Power Materials Knowledge and Lifing Methodologies

This report documents the results of an experimental program conducted on two advanced metallic alloy systems (Rene' 142 directionally solidified alloy (DS) and Rene' N6 single crystal alloy) and the characterization of two distinct internal state variable inelastic constitutive models. The long term objective of the study was to develop a computational life prediction methodology that can integrate the obtained material data. A specialized test matrix for characterizing advanced unified viscoplastic models was specified and conducted. This matrix included strain controlled tensile tests with intermittent relaxtion test with 2 hr hold times, constant stress creep tests, stepped creep tests, mixed creep and plasticity tests, cyclic temperature creep tests and tests in which temperature overloads were present to simulate actual operation conditions for validation of the models. The selected internal state variable models where shown to be capable of representing the material behavior exhibited by the experimental results; however the program ended prior to final validation of the models.

Spring, Samuel D.↗

Thin Film Physical Sensors for High Temperature Applications

For the advanced engines in the future, knowledge of the physical parameters of aerospace components is necessary on the test stand and in flight. NASA GRC is leveraging expertise in thin films and high temperature materials to measure hot section gas and surface temperature, heat flux and static and dynamic strain. The current challenges of instrumentation technology are to further develop systems packaging and component testing of specialized sensors, further develop instrumentation techniques on complex surfaces, improve sensor durability, and to address needs for extreme temperature applications. Applications of thin film ceramic sensors as replacement for noble metals are being investigated. Technologies demonstrated in aeronautics and space applications are outlined.

thin films↗

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring a multitude of capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for a particular mission is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) to defining gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities, gaps, and KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed. The paper will contain a summary of the approximately 60 gaps. Gaps are classified as to their type (architecture, knowledge, technology, developmental, or engineering) depending on the magnitude of the gap. The paper will provide brief overviews of a few major technology challenges and the technologies being considered, but will reference detailed papers for a more thorough treatment of the challenges and state of the art. Data analysis of the gaps is in work and results are not currently available for this abstract. It is anticipated the paper will include examples of select KPPs with descriptions as to why these are the relevant measures. Additionally some KPPs will be graphically presented over time to show progress to date and when performance targets need to be achieved to support exploration missions. Graphical summaries of how gaps closures with near term mission elements support follow-on mission elements will be provided.

Life Support↗

Barefoot Rover: a Sensor-Infused Rover Wheel Demonstrating In-Situ Engineering and Science Extractions using Machine Learning

In this work, we demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.

Marchetti, Yuliya↗

Inventory Management Improvement Project

The Lawrence Livermore National Laboratory (LLNL) conducts research and development for the National Nuclear Security Agency (NNSA) and its affiliates. The Polymer AM team at LLNL conducts research and development in 3D printing, specifically direct-ink-write, in accordance with LLNL and NNSA missions. The team is composed of machine operators, chemists, testing engineers, and project engineers across multiple lab spaces with one shared storage area at LLNL. The operations use a variety of different consumables and hardware to conduct research applications for LLNL and NNSA. These items are critical to performing operation tasks; if an item is out of stock, operations associated with the respective item could be suspended for weeks. As such, the Polymer AM team manages an inventory of spare consumables and hardware to ensure these items are always available. However, the current management system, an excel sheet managed by the project engineer group, is not intuitive in providing inventory information despite the high labor utilization needed to maintain the system. As such, the team is looking to improve their inventory management that can send notifications regarding inventory needs, accessible to other team members, provide all relevant information to a specific item, and store historical information for budget and operation planning. The proposed solution is a Computer Maintenance Management System (CMMS): a web-based management software that stores inventory information and provides automated notifications. The system will store information on each item including quantity in stock, technical information, supplier information, costs, lead times, and expiration date. The system has a notifications function that can send notifications to the respective team member’s when an item needs to be counted, item inventory is low, or an item is approaching their expiration date. Information for each item can be tracked over time creating data to be used for budget planning and process improvement purposes. Due to its web-based source, the system can be accessed by the respective team member viewing technical information, quantity, and purchasing information.

42 ENGINEERING↗

Study of influence of plastic scintillators thicknesses to detect Beta particles and Gamma radiation by means of spectral analysis of {sup 90}Sr, {sup 90}Y and {sup 137}Cs sources

The Nuclear and Energy Research Institute - IPEN, offers post-graduate programs, namely: Nuclear Technology - Applications (TNA), Nuclear Technology - Materials (TNM), Nuclear Technology - Reactors (TNR). The Institute programs mission is to form expert technicians, physicists and engineers with a strong knowledge in their discipline to work in the nuclear area. The course: 'Theoretical Fundamentals and Practices of the Instrumentation used in Nuclear Data Acquisition' covers the use of laboratory nuclear instrumentation and the accomplishment of experiments to obtain nuclear parameters. One of these experimental exercises is object of this work: 'Study of influence of plastic scintillators to detect Beta particles and Gamma radiation by means of spectral analysis of {sup 90}Sr, {sup 90}Y and {sup 137}Cs sources'. The use of scintillators plastic for the detection has the advantage of low cost, high mechanical strength, is not hygroscopic and can be manufactured in large volumes. This work aims to present the analysis of relative efficiency of detection of plastic scintillators of various thicknesses for beta particles and gamma radiation by the spectrum of {sup 137}Cs and {sup 90}Sr. Due to lack of resolution of the detectors plastic scintillators we worked with relative efficiency. The evaluation was done by reading deposited energy, using the software MAESTRO, for each detector thickness. For beta particles was observed an ideal thickness around 3 mm and the better photon efficiency was observed with increasing the thickness of the detector. The present experiment does not intend to establish a new technique for this subject: it solely aims student's practical exercises in nuclear properties of elements and detectors being part of the nuclear experimental course. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Overview of the US Nuclear Science User Facilities

Specialized and often unique and expensive instrumentation, adapted for use on radioactive materials, is essential to conduct research in the area of nuclear energy. Much of this equipment is located in facilities dedicated for such work that have been built and maintained over many decades. The Nuclear Science User Facilities (NSUF) was established in 2007 under the US Department of Energy Office of Nuclear Energy (DOE-NE) in order to bring these capabilities together with those innovative ideas from researchers at universities, national laboratories, small business, and industry that might not have regular access to reactors, hot cells, transportation casks, radiologically qualified instrumentation, and associated expertise. Early descriptions of the originally named Advanced Test Reactor National Scientific User Facility have been given. Through a competitively reviewed proposal process, the NSUF offers access to these capabilities and expertise at no cost to the user to promote research that will address the mission of DOE-NE. As a national organization comprised of a number of partner facilities across the US and located at National Laboratory, university, and industry sites, the NSUF supports materials science studies directed at irradiation effects in nuclear fuels and materials as well as in-pile and post irradiation examination (PIE) instrumentation development. The NSUF has created a Nuclear Fuels and Materials Library (NFML) of previously irradiated materials that users may access for their studies. Expanding the library for future applications of advanced technologies and novel concepts is an important objective of the NSUF. The NSUF has established and maintains the Nuclear Energy Infrastructure Database (NEID) as a tool for both DOE-NE and the nuclear energy research community. The extensive catalogue of capabilities is intended to aid DOE-NE, NSUF, and researchers more effectively and efficiently utilize the available capabilities. (authors)

36 MATERIALS SCIENCE↗

Research and Development Capabilities available through the Nuclear Science User Facilities

The Nuclear Science User Facilities (NSUF), established in 2007 as the Advanced Test Reactor (ATR) National Scientific User Facility is chartered to provide cost-free access to unique and important research and development capabilities and infrastructure to nuclear energy-focused researchers. Originally, the NSUF was formed to utilize excess capacity in the ATR and the Hot Fuels Examination Facility (HFEF) hot cells. In the eight years since its inception, the NSUF has expanded to include most of the capabilities at the Idaho National Laboratory as well as twelve external 'partner' facilities. The inclusion of the partner facilities makes the NSUF the first distributed user facility, a 'laboratory without walls.' Users can apply for access to any of the NSUF INL or partner facilities using the same process, either through the annual Office of Nuclear Energy Consolidated Innovative Nuclear Research funding announcement or the NSUF Rapid Turnaround Experiment (RTE) opportunities, offered three times each year. In support of the capability access mission, the NSUF also offers access to additional resources. In order to help researchers connect with the appropriate capabilities, the NSUF has developed a comprehensive searchable database of nuclear energy R and D infrastructure in the US and worldwide. Additionally, the NSUF hosts a Fuels and Materials Sample Library (FMSL) that includes an ever-expanding set of previously irradiated materials, supporting un-irradiated archive material and fabrication and irradiation data for the materials. The capabilities of the NSUF partner facilities, the NEID, the fuels and materials sample library and the access application information is all available at the NSUF web site: ATRNSUF.INL.gov. (author)

36 MATERIALS SCIENCE↗

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗