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A number of missions have recently been proposed that aim to take advantage of the growing scientific interest in the region of space near libration points in the Sun-Earth system. In support of missions that include increasingly complex trajectories and incorporate libration point orbits, more efficient techniques and new philosophies for design must be considered.
A Power Extension Package (PEP) has been designed to provide additional electrical power and energy during Shuttle sortie missions. The considered investigation was conducted to determine the most suitable allocation of PEP monitoring and control functions between the Orbiter's existing (centralized) Systems Management General Purpose Computer and an embedded PEP processor. PEP monitoring and control functions are examined, and a configuration definition is considered, taking into account the 'functional migration' process, function allocation criteria, and candidate functional configurations. A trade study is conducted, giving attention to an assessment of four candidate configurations. Assessment factors are related to cost, development risk, aspects of reliability and safety, PEP design complexity, PEP/STS integration complexity, flight operations, and launch/landing site operations. A thorough (subjective) assessment of the PEP system life cycle indicates substantial benefits from a distributed processing approach.
Monitoring the Total Organic Carbon (TOC) in spacecraft potable water will be of major importance in long-duration human space exploration. In-flight analysis of potable water produced from a regenerative water processor provides immediate feedback on the quality of reclaimed water for crew health as well as water processing system health monitoring. This paper updates the progress in development of the next generation Total Organic Carbon Analyzer (TOCA) designed for the unique requirements of an exploration-class mission. The current objective is to design, build, certify, deliver, and operate a TOCA technology demonstration on the International Space Station (ISS). The next generation analyzer system technology was previously developed and selected among a feasibility study of other options. The new system provides primary advantages of reduced mass and volume through reduced system complexity and reduced need for consumables; therefore, the flight project is named MiniTOCA. The project has recently completed design of the tech demo instrument and assembled and tested a flight-like engineering development unit. The engineering unit has undergone performance testing and environmental testing which provides confidence for the project to move forward with flight unit production and certification activities. Test results are summarized in this paper. The flight unit is targeted for delivery to ISS in late 2025.
Monitoring the Total Organic Carbon (TOC) in spacecraft potable water will be of major importance in long-duration human space exploration. In-flight analysis of potable water produced from a regenerative water processor provides immediate feedback on the quality of reclaimed water for crew health as well as water processing system health monitoring. This paper updates the progress in development of the next generation Total Organic Carbon Analyzer (TOCA) designed for the unique requirements of an exploration-class mission. The current objective is to design, build, certify, deliver, and operate a TOCA technology demonstration on the International Space Station (ISS). The next generation analyzer system technology was previously developed and selected among a feasibility study of other options. The new system provides primary advantages of reduced mass and volume through reduced system complexity and reduced need for consumables; therefore, the flight project is named MiniTOCA. The project has recently completed design of the tech demo instrument and assembled and tested a flight-like engineering development unit. The engineering unit has undergone performance testing and environmental testing which provides confidence for the project to move forward with flight unit production and certification activities. Test results are summarized in this paper. The flight unit is targeted for delivery to ISS in late 2025.
With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.
Multidisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO.
NASA is currently designing a new space suit capable of working in deep space and on Mars. Designing a suit is very difficult and often requires trade‐offs between performance, cost, mass, and system complexity. To verify that new suits will enable astronauts to perform to their maximum capacity, prototype suits must be built and tested with human subjects. However, engineers and flight surgeons often have difficulty understanding and applying traditional representations of human data without training. To overcome these challenges, NASA is developing modern simulation and analysis techniques that focus on 3D visualization. Early understanding of actual performance early on in the design cycle is extremely advantageous to increase performance capabilities, reduce the risk of injury, and reduce costs. The primary objective of this project was to test modern simulation and analysis techniques for evaluating the performance of a human operating in extra‐vehicular space suits.
Two new refractory amorphous high-entropy alloys (RAHEAs) within the W–Ta–Cr–V and W–Ta–Cr–V–Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using in situ Transmission Electron Microscopy. While the 14W-41Ta-26Cr-19V in at.% RAHEA (defined as WTaCrV RAHEA) was found to be unstable under such tests, additions of Hf in this system composing a new quinary 24W-40Ta-18Cr-5V-13Hf in at.% RAHEA (defined as WTaCrVHf RAHEA) was found to be a route to achieve stability both under annealing and irradiation. A new effect of nanoprecipitate reassembling observed to take place within the WTaCrVHf RAHEA under irradiation indicates that a duplex microstructure composed of an amorphous matrix with crystalline nanometer-sized precipitates enhances the radiation response of the system. Further, it is demonstrated that tunable chemical complexity arises as a new alloy design strategy to foster the use of novel RAHEAs within extreme environments. New perspectives for the alloy design and application of chemically-complex amorphous metallic alloys in extreme environments are presented with focus on their thermodynamic phase stability when subjected to high-temperature annealing and displacing irradiation.
During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.
Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.
Focal Areas: (2) Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (3)Insight gleaned from complex data (both observed & simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI
Focal Area(s): Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models (Primary); insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics or knowledge-guided AI (Secondary). Science Challenge: Wildfires modify land surface characteristics, such as vegetation composition, soil and litter carbon stocks, and surface albedo, with significant consequences for the regional carbon cycle. For example, tropical regions (i.e., African and South America) are particularly vulnerable to wildfire, account for more than 80% of the global burned area, and emit ~1.4 PgC y -1 into the atmosphere together with other dust and aerosols that strongly affect regional climate.
Global Thermostat (GT) has developed a process that addresses the primary technical challenges associated with direct air capture (DAC): the ability to process enormous volumetric flowrates of air and provide the energy for regeneration at acceptable cost. However, at current, there is opportunity for improvement in overall capture costs and especially in capital costs. While GT has advanced its base technology to TRL levels supporting commercial deployments, its research strategy includes alternative technology embodiments that enable substantial reductions in the cost per tonne of CO 2 removed. The objective of this project is to advance the most promising of these embodiments, where a DAC plant is operated in a continuous fashion rather than a discrete stepwise fashion (GT’s commercial scale technology approach). The Continuous Motion Direct Air Capture (cDAC) System’s advantages over the GT baseline stepwise DAC platform have been proposed primarily as a reduction in the complexity required for starting and stopping a movement system, relaxing requirements for other components designed for a rapid switching application, and a flattening of the sharp instantaneous fluid flowrates into steady-state mass & energy flows to enable smoother operation and easier heat integration. These advantages can lead to shorter cycle times, greater plant reliability, and lower capital expense. The primary objective of this project is the design, construction, commissioning, and operation of a field-test unit (FTU) at a scale in the range of ~200 tons CO 2 per year. Data generated from the operation campaign would then be used in a prescreening techno-economic analysis (TEA) and life cycle analysis (LCA), allowing this process to be compared to other carbon capture technologies.
Two-volume edition of the papers of the symposium is described. It is divided into six sections - parts, materials, management, system testing, component design, and system test. Material presented focuses attention on problems created by the increased complexity of technology and long-term mission requirements.
Electromagnetic processes peculiar to the direct-strike case are reviewed with respect to their implications for lightning electromagnetic simulation. At low frequencies (quasistatic) there are important surface-charge-density and corona effects in addition to the surface-current-density effects. At resonant frequencies the frequency-spectral content of the excitation and properties of the arc (attachment, detachment, time history, spatial distribution, resistance, etc.) are significant. Of great complexity in all this are nonlinear aspects of the arc and corona around the system of interest. The complexity of these various processes requires rigor in the simulator design. Potential simulation concepts are presented and their relative merits are discussed.
The AFTI/F-16 flight test program is summarized, and several design issues of general interest are addressed. A brief description is given of the test vehicle, its flight control modes, and the flight envelopes in which testing was performed. Flight test results are summarized by addressing benefits experienced in flight control task-tailoring, handling qualities in mission tasks, aircraft structure considerations, digital flight control system performance, and human factors. Finally, several design issues relevant to future fighter aircraft are examined, including degraded flight control, system complexity, simplex information in redundant systems, and single failure propagation in redundant systems.
The complexity of codes for solutions of real aerodynamic problems has progressed from simple two-dimensional models to three-dimensional inviscid and viscous models. As the algorithms used in the codes increased in accuracy, speed and robustness, the codes were steadily incorporated into standard design processes. The highly sophisticated codes, which provide solutions to the truly complex flows, require computers with large memory and high computational speed. The advent of high-speed supercomputers, such that the solutions of these complex flows become more practical, permits the introduction of the codes into the design system at an earlier stage. The results of several codes which either were already introduced into the design process or are rapidly in the process of becoming so, are presented. The codes fall into the area of turbomachinery aerodynamics and hypersonic propulsion. In the former category, results are presented for three-dimensional inviscid and viscous flows through nozzle and unducted fan bladerows. In the latter category, results are presented for two-dimensional inviscid and viscous flows for hypersonic vehicle forebodies and engine inlets.
The Galileo mission and spacecraft, consisting of a Jupiter-orbiter and an atmospheric entry probe, are discussed. Components will include: magnetometers and plasma-wave antennas on a boom, high-gain antenna, probe vehicle, two different bus electronics packages, and a radioisotope thermoelectric generator. Instruments, investigators and objectives are tabulated for both probe science and orbiter science investigations. Requirements in the design of the attitude and articulation control system are very stringent because of the complex dynamics, flexible body effects, the need for autonomy, and the severe radiation environment in the Jupiter nighborhood. Galileo was intended to be ready for launch via Space Shuttle in May of 1986.