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The GRACE Mission: Meeting the Technical Challenges
The Gravity Recovery and Climate Experiment (GRACE) mission is scheduled for launch in June 2001.
Technical challenges in the development of Jupiter-bound interplanetary spacecraft
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Urban Air Mobility: A Control-Centric Approach to Addressing Technical Challenges
Urban Air Mobility (UAM) is an emerging aviation sector and is playing an integral part in the on-demand mobility revolution. UAM is powered by the convergence of advances in distributed electrical propulsion (DEP) and vehicle autonomy. The complexity of operations in the urban environment and the unconventional vehicle configurations designed to take advantage of new propulsion technologies, result in numerous challenges that benefit from a control-centric approach. In this talk we outline some of these challenges and present our current approach to addressing them. For example, in order to achieve full market potential and access to UAM, vehicle autonomous flight is required. A key barrier to autonomous flight in a large multi-agent system is dealing with off-nominal situations and contingencies in a safe and predictable manner. We present our approach to intelligent contingency management, and share recent results and open problems. Additionally, we discuss another major barrier to ubiquitous UAM – the noise signature produced by vehicles with multiple rotors. We present our approach to minimizing such noise within the framework of the acoustically-aware vehicle.
Cluster after 20 Years of Operations: Science Highlights and Technical Challenges
The Cluster mission was the first constellation using four identical spacecraft to study Sun-Earth connection plasma processes. Using four spacecraft in a tetrahedron shape, it could measure, for the first time, 3D quantities such as electrical currents, plasma gradients or divergence of the electron pressure tensor and 3D structures such as boundaries, surface waves or vortices. Launched in pairs in July and August 2000, on two Soyuz rockets from Baikonur, the four spacecraft have been collecting data continuously for more than 20 years. The mission faced many challenges during the years of operations as some spacecraft subsystems had a lifetime of a few years beyond the initial two-year mission. The major one was to operate without functioning batteries and to successfully pass short and long eclipses, up to 3 h long, without damaging the on-board computers and transmitters and without freezing the fuel. More than 1,000 eclipses have been successfully passed since 2010 using a specially made procedure which switches off the complete spacecraft before entering into eclipse and switches it on when the Sun is again illuminating the solar panels. During 20 years, many discoveries and science results have been published in more than 2,700 scientific papers. A few highlights are presented here, focusing on how varying the spacecraft separation was essential to achieve the science goals of the mission. The Cluster Science Data System and the Cluster archive allows public access to all science data as well as spacecraft ancillary data.
Building a Land Data Assimilation Community to Tackle Technical Challenges in Quantifying and Reducing Uncertainty in Land Model Predictions
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Close out the Critical Commitment for System Wide Safety’s Technical Challenge 3 (TC 3)
- Deliver validated methods and recommended practices to reduce certification costs for ground and onboard vehicle guidance and control systems through expanded acceptability of analysis as evidence for certification FY 2022. - Communicate results to maximize public awareness of the research and transfer capabilities via a set of on-demand training seminars and supporting materials including reports, publications and open source software codes where applicable.
Technical Challenge 1 In-Time Terminal-Area Risk Management
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Introducing the NASA AATT EQuIP Technical Challenge
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IER 479: Technical Challenges of a Low Temperature Experiment and Proposed Solutions
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Developing & Investigating Subsurface Storage Potential and Assessing Technical Challenges for Hydrogen
Conference abstract
IDENTIFYING TECHNICAL CHALLENGES IN SAFEGUARDS MEASUREMENTS OF ADVANCED SMALL MODULAR REACTOR FUEL ELEMENTS
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Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations
The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.
Version 0 EOSDIS - An overview
Attention is given to NASA's Earth Observing System Data and Information System (EOSDIS), which is to be a single, distributed but internally consistent evolutionary system to support the planning and execution of EOS data acquisitions and to process, archive, and distribute EOS data products and selected non-EOS data to enable interdisciplinary studies of the earth. V0 EOSDIS, a logical step in this evolutionary process, is to address both technical and managerial challenges. Technical challenges include developing a multidiscipline, distributed system for searching and ordering data in a heterogeneous environment, and standardizing data formats and distribution techniques among differing communities and organizations. Managerial challenges include establishing and maintaining a structure consisting of geographically distributed entities such that cooperative development is carried out effectively despite organizational differences, maintaining interactions with the scientific community to ensure its close involvement despite its size and diversity, and keeping the expectations for V0 consistent with its schedules and resources.
Virtual Project Management Challenge
Technical knowledge is essential to the work done by NASA practitioners. So it may be surprising to learn that the most ingenious and elegant solutions to project challenges often arise not from a specific technical discipline perspective, but from a systems-focused mindset. While technical discipline expertise is a critical component of project success, sometimes the simplest resolution to a problem involves a systems-wide solution. Because of this, encouraging a systems mentality among project team members can be a powerful tool in mitigating risk and eliminating threats. Join us for an exploration of the critical ways in which a systems engineering and integration perspective can enhance project management efforts. Presenter Bo Bejmuk is the former Space Shuttle Orbiter Program Director and manager of Sea Launch Program operations and development for Boeing. He recently served as Chairman of the Standing Review Board for the NASA Constellation Program. Moderator Ramien Pierre is from NASA's Academy for Program/Project and Engineering Leadership (APPEL).
Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data
Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the
Welding of Haynes 282 to Steels to Enable Modular Rotors for Advanced Ultra Super-Critical Steam Turbines
Steam turbines for an Advanced Ultra Super Critical (AUSC) fossil fired power plant will operate at temperatures well above those of current commercial steam cycles with inlet temperatures more than 760 C , which is beyond the capabilities of alloy steels presently used for steam turbine applications and requires advanced materials. Large components such as steam turbine rotors may be made of nickel based super alloys such as Haynes 282 (H282). However, monolithic forgings of superalloys in the sizes required for large steam turbines rotors can be prohibitively expensive besides many technical challenges. To minimize cost and alleviate the related technical challenges, superalloy use needs to be limited to locations on the steam turbine rotor where strength and temperature requirements cannot be met by conventional steels. This is possible if nickel-based superalloys can be successfully welded to steels and the related technical challenges - machining parts made of dissimilar welded materials, non-destructive examination of such welds for flaw detection; and, material properties of such hybrid components – are sufficiently addressed. In this technology development project, we successfully welded H282 to plates up to ~ 75 mm (~ 3 inches) to a 3.5NiCrMoV steel of similar thickness. Advanced ultrasonic inspection technique called Phased Array Ultrasonic Testing (PAUT) was employed to examine the dissimilar H282-Steel welds, into which flat bottomed side drilled holes (SDH) of various diameters were introduced, to determine the minimum detectable feature sizes; it was shown that with PAUT SDH of dia. down to 0.5 mm could be detected in the base alloys and SDH with dia. down to 2.4 mm could be detected in the weld metal under multiple orientations successfully. An autonomous machining process monitoring system was developed and demonstrated whereby the forces acting on the cutting tool could be actively monitored as the cutting tool transitioned from H282 to Steel across the weld using which the machining parameters can be potentially altered without interruption to extend tool life. This project successfully achieved its objectives of - i. Developing a welding methodology and viable welding geometries, to successfully join H282 to steel 3.5CrMoNiV steel to enable manufacture of modular steam turbine rotors for AUSC applications (conditions of at least 760 °Celsius and 3,100 psia (pounds per square inch absolute pressure) and evaluate the material properties of the welded specimen. ii. Employ the advanced ultrasonic inspection technique to the dissimilar weld metal joint and determine the minimum detectable feature sizes. iii. Develop effective machining techniques to machine such hybrid structures with online tool force monitoring and effect machine state metrics for optimal results.