Computational Modeling of Microstructure Formation During Laser Powder Bed Fusion of Bulk Thermoelectric Materials
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Viewgraphs are used to illustrate the reliability engineering and aerospace safety of the Space Transportation Main Engine (STME). A technology developed is called Total Quality Management (TQM). The goal is to develop a robust design. Reducing process variability produces a product with improved reliability and safety. Some engine system design characteristics are identified which improves reliability.
Biomedical engineering principles applied to medicine and biology
NASA has come a long way in our journey to reduce the risks of operating the Spse Shuttle system. The External Tank bipod Thermal Protection System has been redesigned to eliminate the proximate cause of the Columbia accident. In all areas, we have applied the collective knowledge and capabilities of our Nation to comply with the Columbia Accident Investigation Board recommendations and to raise the bar beyond that. We have taken prudent technical action on potential threats to review and verify the material condition of all critical areas where failure could result in catastrophic loss of the crew and vehicle. We are satisfied that critical systems and elements should operate as intended-safely and reliably. While we will never eliminate all the risks from our human space flight programs, we have eliminated those we can and reduced, controlled, and/or mitigated others. The remaining identified risks will be evaluated for acceptance. Our risk reduction approach has its roots in the system safety engineering hierarchy for hazard abatement long employed in aerospace systems engineering. The components of the hierarchy are, in order of precedence, to: design/redesign; eliminate the hazard/risk; reduce the hazard/risk; and control the hazard/risk and/or mitigate the consequence of the remaining hazard/risk through warning devices, special procedures/capabilities, and/or training. This proven approach to risk reduction has been applied to potential hazards and risks in all critical areas of the Space Shuttle and has guided us through the technical challenges, failures, and successes present in return to flight endeavors. This approach provides the structured deliberation process required to verify and form the foundation for accepting any residual risk across the entire Space Shuttle Program by NASA leadership.
Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.
Engineering technology programs are characterized by their focus on application and practice, and by their approximately 50/50 mix of theory and laboratory experience. Engineering technology graduates are employed across the technological spectrum and are often found in areas that deal with application, implementation, and production. Yet we know very little about the communications practices and information-use skills of engineering technology students. In this paper, we report selected results of an exploratory study of engineering technology students enrolled in three U.S. institutions of higher education. Data are presented for the following topics: career goals and aspirations; the importance of, receipt of, and helpfulness of communications and information-use skills instruction; collaborative writing; use of libraries; and the use of electronic (computer) networks.
A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.
The primary goal of the workshop was to bring together formal methods researchers and aerospace industry engineers to investigate new opportunities for applying formal methods to aerospace problems. The first part of the workshop was tutorial in nature. The second part of the workshop explored the potential of formal methods to address current aerospace design and verification problems. The third part of the workshop involved on-line demonstrations of state-of-the-art formal verification tools. Also, a detailed survey was filled in by the attendees; the results of the survey are compiled.
The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.
The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.
Educational requirements for aerospace structures research
Maverick Corporation, of Blue Ash, Ohio, licensed DMBZ-15 polyimide technology from Glenn Research Center. This ultrahigh-temperature material provides substantial weight savings and reduced machining costs compared to the same component made with more traditional metallic materials. DMBZ-15 has a wide range of applications from aerospace (aircraft engine and airframe components, space transportation systems, and missiles) to non-aerospace (oil drilling, rolling mill), and is particularly well-suited to use as face sheets with honey cones or thermal protection systems for reusable launch vehicles, which encounter elevated temperatures during launch and re-entry.
Specified here are the functional and informational requirements for software modules which address the geometric and data modeling needs of the aerospace structural engineer. The modules are to be included as part of the Solid Modeling Aerospace Research Tool (SMART) package developed for the Vehicle Analysis Branch (VAB) at the NASA Langley Research Center (LaRC). The purpose is to precisely state what the SMART Structures modules will do, without consideration of how it will be done. Each requirement is numbered for reference in development and testing.
KSC-GP-435,Engineering Drawing Practices, Volume I of II, Aerospace and Ground Support Equipment, establishes the conventions to be adhered to by engineering and drafting personnel in the preparation, revision, and completion of engineering digital product definition data sets. This manual sets forth the minimum requirements acceptable at Kennedy Space Center (KSC) for the preparation of model-only, model and dependent drawing, and drawing-only digital product definition data sets based on the engineering drawing and model requirements in the ASME Y14 series.
Design documents are intended to outline the goalsof a system or project, which are utilized in the creation ofspecific software requirements. At the NASA Jet PropulsionLaboratory, California Institute of Technology, Functional DesignDescription (FDD) documents describe the scope of theproject and reflect the design and implementation of the system.The specifications in the document are not explicitly writtenas requirements, though these guidelines must be reflected inthe official software requirements. In this work we present afully automatic approach to extracting software requirementsfrom design documents as well as comparing the extractedrequirements to those that exist in the official software requirementdatabase. We do this through (1) sentence extractionfrom the design document, (2) the incorporation of coreferenttext, and (3) aligning the extracted text to the official softwarerequirements. Via natural language processing and informationretrieval techniques, our system results in an automated processthat ensures that the specifications in the design document resultin official software requirements. We find that extraction ofimperatives results in a recall rate of 0.73 and the TF-IDF cosinesimilarity metric is shown to be a useful and successful way tocompare requirements.Though there has been recent work investigating the usefulnessof natural language processing techniques in requirement engineering,this has not been made use of in the aerospace industry.Aerospace requirement engineering is a field particularly ripefor this type of innovation because these techniques can bothautomate some of needlessly manual work and contribute toaerospace safety practices by identifying issues that a humanmay miss. We present the first fully automated approach thatextracts requirements from a design document and comparesthem to a database, and use these findings as encouragementfor future work that makes use of natural language processingtechniques in aerospace requirement engineering.
A manual is presented for use by counselors in career guidance programs. Pertinent information is provided on choices open in aerospace sciences, engineering, and technology. Accredited institutions awarding degrees in pertinent areas are listed as well as additional sources of aerospace career information. NASA's role and fields of interest are emphasized.
The NASA Glenn Research Center and its industry partners are developing a Common Object Request Broker (CORBA) Security (CORBASec) test bed to secure their distributed aerospace propulsion simulations. Glenn has been working with its aerospace propulsion industry partners to deploy the Numerical Propulsion System Simulation (NPSS) object-based technology. NPSS is a program focused on reducing the cost and time in developing aerospace propulsion engines. It was developed by Glenn and is being managed by the NASA Ames Research Center as the lead center reporting directly to NASA Headquarters' Aerospace Technology Enterprise. Glenn is an active domain member of the Object Management Group: an open membership, not-for-profit consortium that produces and manages computer industry specifications (i.e., CORBA) for interoperable enterprise applications. When NPSS is deployed, it will assemble a distributed aerospace propulsion simulation scenario from proprietary analytical CORBA servers and execute them with security afforded by the CORBASec implementation. The NPSS CORBASec test bed was initially developed with the TPBroker Security Service product (Hitachi Computer Products (America), Inc., Waltham, MA) using the Object Request Broker (ORB), which is based on the TPBroker Basic Object Adaptor, and using NPSS software across different firewall products. The test bed has been migrated to the Portable Object Adaptor architecture using the Hitachi Security Service product based on the VisiBroker 4.x ORB (Borland, Scotts Valley, CA) and on the Orbix 2000 ORB (Dublin, Ireland, with U.S. headquarters in Waltham, MA). Glenn, GE Aircraft Engines, and Pratt & Whitney Aircraft are the initial industry partners contributing to the NPSS CORBASec test bed. The test bed uses Security SecurID (RSA Security Inc., Bedford, MA) two-factor token-based authentication together with Hitachi Security Service digital-certificate-based authentication to validate the various NPSS users. The test bed is expected to demonstrate NPSS CORBASec-specific policy functionality, confirm adequate performance, and validate the required Internet configuration in a distributed collaborative aerospace propulsion environment.
Northeast High Magnet School of Philadelphia, Pennsylvania is a proud sponsor of the Space Research Center (SPARC). SPARC, a model program of the Medical, Engineering, and Aerospace Magnet school, provides talented students the capability to successfully exercise full simulations of NASA manned missions. These simulations included low-Earth Shuttle missions and Apollo lunar missions in the past, and will focus on a planetary mission to Mars this year. At the end of each scholastic year, a simulated mission, lasting between one and eight days, is performed involving 75 students as specialists in seven teams The groups are comprised of Flight Management, Spacecraft Communications (SatCom), Computer Networking, Spacecraft Design and Engineering, Electronics, Rocketry, Robotics, and Medical teams in either the mission operations center or onboard the spacecraft. Software development activities are also required in support of these simulations The objective of this paper is to present the accomplishments, technology innovations, interactions, and an overview of SPARC with an emphasis on how the program's educational activities parallel NASA mission support and how this education is preparing student for the space frontier.