SEARCH · Engineering Papers
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.
The control of the rendezvous vehicle during proximity operations is considered. It is shown how fuzzy sets can be used for autonomous vehicle control to model the human capability of common sense reasoning. Such models are integrated with expert systems and engineering control systems technology to create a system that performs comparably to a manned system.
Fully automated variable-polarity plasma arc VPPA welding system developed at Marshall Space Flight Center. System eliminates defects caused by human error. Integrates many sensors with mathematical model of the weld and computer-controlled welding equipment. Sensors provide real-time information on geometry of weld bead, location of weld joint, and wire-feed entry. Mathematical model relates geometry of weld to critical parameters of welding process.
A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.
The increasing complexity of engineering systems has sparked increasing interest in multidisciplinary optimization (MDO). This paper presents a survey of recent publications in the field of aerospace where interest in MDO has been particularly intense. The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focussed on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design-oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the authors' main expertise being in the structures area, the bulk of the references focus on the interaction of the structures discipline with other disciplines. In particular, two sections at the end focus on two such interactions that have recently been pursued with a particular vigor: Simultaneous Optimization of Structures and Aerodynamics, and Simultaneous Optimization of Structures Combined With Active Control.
This report presents tile results of an experimental and analytical study of human performance in uncoupled and coupled control systems. Human pilot performance in single and two-axis systems was mathematically modeled by linear second-order describing functions. Model parameters were determined using model matching techniques. Analysis of the models showed that the amplitude ratio and phase lead of the describing function increased with training indicating an increase in open loop bandwidth. The phase margin also decreased with training. Increasing the plant lag time constant resulted in an increase in the model lead time constant and a decrease in the zero frequency gain. No significant difference was found to exist in the normalized tracking error per axis between the two-axis tasks and the single-axis tasks. However tile model lead time constant was significantly greater in two-axis tracking. Manual tracking of two-axis systems with cross-coupling was studied experimentally and analytically. Approximate methods for modeling two-axis performance were developed and checked using a precise spectral analysis approach. Coupled and uncoupled, symmetrical and asymmetrical two-axis performance was compared. The results show that modeling of cross-coupled systems is feasible and that trained subjects are capable of decoupling the axes of some systems. A methodology study compared the identification performance of continuous, iterative, and extrapolation model matching techniques. An iterative technique employing sensitivity equations for the generation of influence coefficients was found to be the best technique due to its excellent identification accuracy and ease of implementation. Convergence in iterative techniques can be improved substantially by equalizing the parameter adjustment rates and limiting the maximum correction per iteration.
From our earlier work, we demonstrated a circulating microRNA (miRNA) signature that is present and involved with the general increased health risks during spaceflight. From this work we demonstrated that this miRNA signature impacted the overall biology and health with both the microgravity and space radiation components of the space environment. We showed that this miRNA signature can be an optimal biomarker for health risk and also has potential to be utilized as a countermeasure to mitigate the damage caused by the space environment by utilizing a human 3D microvascular tissue model. By applying a novel self-delivery system to target 3 miRNAs (i.e. antagomirs) from our spaceflight miRNA signature impacting cardiovascular health risks, we were able to completely mitigate damage caused by exposure to simulated Galactic Cosmic Ray (GCR) irradiation. Here we further expand on the countermeasure experiments to uncover the specific novel biology involved with this countermeasure and in vivo experiments that demonstrates that these antagomirs rescue damage caused to certain organs due to both microgravity and space radiation. Specifically, the miRNAs rescued damage to the heart and immune suppression that occurred in addition to other key biology. In addition, we have also observed with the 3D microvascular tissue model improved DNA double strand break repair machinery which can also contribute to improved recovery and protection against damage caused by space radiation. This work expands on our previous work and further uncovers how a potential minimally invasive countermeasure can be used to mitigate space environment effects.
From our earlier work, we demonstrated a circulating microRNA (miRNA) signature that is present and involved with the general increased health risks during spaceflight. From this work we demonstrated that this miRNA signature impacted the overall biology and health with both the microgravity and space radiation components of the space environment. We showed that this miRNA signature can be an optimal biomarker for health risk and also has potential to be utilized as a countermeasure to mitigate the damage caused by the space environment by utilizing a human 3D microvascular tissue model. By applying a novel self-delivery system to target 3 miRNAs (i.e. antagomirs) from our spaceflight miRNA signature impacting cardiovascular health risks, we were able to completely mitigate damage caused by exposure to simulated Galactic Cosmic Ray (GCR) irradiation. Here we further expand on the countermeasure experiments to uncover the specific novel biology involved with this countermeasure and in vivo experiments that demonstrates that these antagomirs rescue damage caused to certain organs due to both microgravity and space radiation. Specifically, the miRNAs rescued damage to the heart and immune suppression that occurred in addition to other key biology. In addition, we have also observed with the 3D microvascular tissue model improved DNA double strand break repair machinery which can also contribute to improved recovery and protection against damage caused by space radiation. This work expands on our previous work and further uncovers how a potential minimally invasive countermeasure can be used to mitigate space environment effects.
As humankind endeavors to travel farther away from Earth, many questions remain to be solved to ensure proper preparation for deep space. Multiple spaceflight stressors can elicit adverse health outcomes including exposure to space radiation. Space radiation exposure has been identified by the National Aeronautics and Space Administration (NASA) as an important contributor to cancer, degenerative tissue diseases including cataracts, cardiovascular disease, immune system dysfunction and possible central nervous system decrements. The complexity of the human central nervous system makes it difficult to adequately recapitulate in experimental model systems, which hinders quantitative description of associated decrements. The brain aging hallmarks, as introduced by Mattson and Arumugam in 2018, are measurable cellular and molecular hallmarks that generally contribute to the aging process, describe an aging phenotype, and are part of the etiology of age-related neurodegenerative diseases. These hallmarks include mitochondrial dysfunction, accumulation of oxidatively damaged molecules (oxidative stress), impaired lysosome and proteasome function, dysregulation of neuronal calcium homeostasis, compromised adaptive cellular stress response, aberrant neuronal network activity, impaired deoxyribonucleic acid (DNA) repair, inflammation, impaired neurogenesis and dysregulated energy metabolism. Cellular senescence and telomere attrition may also be considered, though more evidence is needed to regard them as brain-specific hallmarks of aging. Radiation exposure has previously been correlated with aging etiology; therefore, investigating the effects of radiation exposure within the context of the hallmarks of brain aging may provide insights into potential health risks facing NASA astronauts, and may provide a means to identify disease processes that may be important targets for disease prevention or intervention. This work describes the hallmarks of brain aging and serves as a primer for future investigation into how the hallmarks of brain aging may compare and contrast with outcomes associated with exposure to the space radiation environment. Further, it will be useful in future identification of hallmarks that may be appropriate to target for radiation countermeasures specific to the central nervous system.
From our earlier work, we demonstrated a circulating microRNA (miRNA) signature that is present and involved with the general increased health risks during spaceflight. From this work we demonstrated that this miRNA signature impacted the overall biology and health with both the microgravity and space radiation components of the space environment. We showed that this miRNA signature can be an optimal biomarker for health risk and also has potential to be utilized as a countermeasure to mitigate the damage caused by the space environment by utilizing a human 3D microvascular tissue model. By applying a novel self-delivery system to target 3 miRNAs (i.e. antagomirs) from our spaceflight miRNA signature impacting cardiovascular health risks, we were able to completely mitigate damage caused by exposure to simulated Galactic Cosmic Ray (GCR) irradiation. Here we further expand on the countermeasure experiments to uncover the specific novel biology involved with this countermeasure and in vivo experiments that demonstrates that these antagomirs rescue damage caused to certain organs due to both microgravity and space radiation. Specifically, the miRNAs rescued damage to the heart and immune suppression that occurred in addition to other key biology. In addition, we have also observed with the 3D microvascular tissue model improved DNA double strand break repair machinery which can also contribute to improved recovery and protection against damage caused by space radiation. This work expands on our previous work and further uncovers how a potential minimally invasive countermeasure can be used to mitigate space environment effects.
Earth system models (ESMs) are key tools for providing climate projections under different scenarios of human-induced forcing. ESMs include a large number of additional processes and feedbacks such as biogeochemical cycles that traditional physical climate models do not consider. Yet, some processes such as cloud dynamics and ecosystem functional response still have fairly high uncertainties. In this article, we present an overview of climate feedbacks for Earth system components currently included in state-of-the-art ESMs and discuss the challenges to evaluate and quantify them. Uncertainties in feedback quantification arise from the interdependencies of biogeochemical matter fluxes and physical properties, the spatial and temporal heterogeneity of processes, and the lack of long-term continuous observational data to constrain them. We present an outlook for promising approaches that can help to quantify and to constrain the large number of feedbacks in ESMs in the future. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research (researchers, lecturers, and students). This study updates and significantly expands upon the last comprehensive overview of climate feedbacks in ESMs, which was produced 15 years ago (NRC, 2003).
This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.
Optimal control system theory applied to manual control systems - adaptive control - mathematical models
A series of experiments examining the effect of contrast on the perception of moving plaids is performed. This was done to test the hypothesis put forth by Adelson and Movshon (1982) that the human visual system determines the direction of a moving plaid in a two-staged process: decomposition into component motion followed by application of the intersection of constraints rule. When the gratings within the plaid are of different contrast, the perceived direction is not predicted by the intersection of constraints rule. There is a strong (up to 20 deg) bias in the direction of the higher-contrast grating. A revised model, which incorporates a contrast-dependent weighting of perceived grating speed as observed for one-dimensional patterns (Thompson, 1982), can quantitatively predict most of the results. Results are discussed in the context of various models of human visual motion processing and of physiological responses of neurons in the primate visual system.
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.
Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).
The NASA Engineering Safety Center (NESC) Systems Engineering (SE) Technical Discipline Team (TDT) initiated the Model Based Systems Engineering (MBSE) Pathfinder effort in FY16. The goals and objectives of the MBSE Pathfinder include developing and advancing MBSE capability across NASA, applying MBSE to real NASA issues, and capturing issues and opportunities surrounding MBSE. The Pathfinder effort consisted of four teams, with each team addressing a particular focus area. This paper focuses on Pathfinder team 1 with the focus area of architectures and mission campaigns. These efforts covered the timeframe of February 2016 through September 2016. The team was comprised of eight team members from seven NASA Centers (Glenn Research Center, Langley Research Center, Ames Research Center, Goddard Space Flight Center IV&V Facility, Johnson Space Center, Marshall Space Flight Center, and Stennis Space Center). Collectively, the team had varying levels of knowledge, skills and expertise in systems engineering and MBSE. The team applied their existing and newly acquired system modeling knowledge and expertise to develop modeling products for a campaign (Program) of crew and cargo missions (Projects) to establish a human presence on Mars utilizing In-Situ Resource Utilization (ISRU). Pathfinder team 1 developed a subset of modeling products that are required for a Program System Requirement Review (SRR)/System Design Review (SDR) and Project Mission Concept Review (MCR)/SRR as defined in NASA Procedural Requirements. Additionally, Team 1 was able to perform and demonstrate some trades and constraint analyses. At the end of these efforts, over twenty lessons learned and recommended next steps have been identified.
A two-port impedance-network model of a single-degree-of-freedom remote manipulation system in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. The design of the network involves the selection of feedback gains for the servomechanisms that transmit motion and force information from one port of the two-port to the other in both directions. The proposed methodology allows this selection to be based on both stability requirements and specifications of desired port impedances, given models of the task and the human operator. The resulting design guidelines guarantee stability for any passive task object at the slave port and any passive human impedance at the master port.