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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.
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New method are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model result. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and three dimensional model results interactively.
Abstract Gravitational lensing by galaxy clusters has emerged as a powerful tool to probe the standard cold dark matter (CDM) paradigm of structure formation in the Universe. Despite the remarkable explanatory power of CDM on large scales, tensions with observations on small scales have been reported. Recent studies find that the observational cross section for galaxy–galaxy strong lensing (GGSL) in clusters exceeds the CDM prediction by more than an order of magnitude and persists even after rigorous examination of various possible systematics. We investigate the impact of modifying the internal structure of cluster dark matter subhalos on GGSL and report that altering the inner density profile, given by r γ , to steeper slopes with γ > 2.5 can alleviate the GGSL discrepancy. This is steeper than slopes obtained with the inclusion of the contribution of baryons to the inner regions of these subhalos. Deviating from the γ ~ 1.0 cusps that CDM predicts, these steeper slopes could arise in models of self-interacting dark matter undergoing core collapse. Our results motivate additional study of subhalo core collapse in dense cluster environments.
StarView is the user interface being developed for the Hubble Space Telescope Data Archive and Distribution Service (ST DADS). ST DADS is the data archive for HST observations and a relational database catalog describing the archived data. Users will use StarView to query the catalog and select appropriate datasets for study. StarView sends requests for archived datasets to ST DADS which processes the requests and returns the database to the user. StarView is designed to be a powerful and extensible user interface. Unique features include an internal relational database to navigate query results, a form definition language that will work with both CRT and X interfaces, a data definition language that will allow StarView to work with any relational database, and the ability to generate adhoc queries without requiring the user to understand the structure of the ST DADS catalog. Ultimately, StarView will allow the user to refine queries in the local database for improved performance and merge in data from external sources for correlation with other query results. The user will be able to create a query from single or multiple forms, merging the selected attributes into a single query. Arbitrary selection of attributes for querying is supported. The user will be able to select how query results are viewed. A standard form or table-row format may be used. Navigation capabilities are provided to aid the user in viewing query results. Object oriented analysis and design techniques were used in the design of StarView to support the mechanisms and concepts required to implement these features. One such mechanism is the Model-View-Controller (MVC) paradigm. The MVC allows the user to have multiple views of the underlying database, while providing a consistent mechanism for interaction regardless of the view. This approach supports both CRT and X interfaces while providing a common mode of user interaction. Another powerful abstraction is the concept of a Query Model. This concept allows a single query to be built form a single or multiple forms before it is submitted to ST DADS. Supporting this concept is the adhoc query generator which allows the user to select and qualify an indeterminate number attributes from the database. The user does not need any knowledge of how the joins across various tables are to be resolved. The adhoc generator calculates the joins automatically and generates the correct SQL query.
A review is presented of developments in ecosystem theory, remote sensing, and geographic information systems that support new endeavors in spatial modeling. A paradigm has emerged to predict ecosystem behavior based on understanding responses to multiple resources. Ecosystem models couple primary production to decomposition and nutrient availability utilizing this paradigm. It is indicated that coupling of transport and ecosystem processes alters the behavior of earth system components (terrestrial ecosystems, hydrology, and the atmosphere) from that of an uncoupled model.
Jet substructure observables hold the keys to identifying the inner working of the quark–gluon plasma through its imprints in jet modification patterns. Because of the multi-scale nature of jet evolution, the strategy has focused on developing jet reclustering-based and jet shape-based observables to specifically probe different stages of jet evolution, which provide multi-dimensional quantification of jet particle distribution phase spaces. The developments of jet substructure in the past few years allowed us to explore the correlations among jet observables. The richer information beyond single-observable modifications could give provides a crucial step beyond the energy loss paradigm. This review surveys the theory and phenomenology of modern jet substructure observables, which help constraining the energy scales of medium interactions and identifying heavy flavor quarks within jets. Also, the peculiar soft activities point to more refined studies of medium responses to jets.
The purpose of this study was to determine the effects of a novel combination of mechanical activity paradigms on the isomyosin distribution in rat hindlimb muscles. Thirty female Sprague-Dawley rats were divided into five experimental groups as follows: normal control, functional overload (OV) of the plantaris, OV in conjunction with hindlimb suspension (OV-S), and a combination of OV-S and either static standing weight-bearing activity (OV-SS) or high-incline treadmill exercise (OV-SE). OV of the plantaris resulted in significant hypertrophy and significant fast-to-slow isomyosin shifts. These changes were completely inhibited by the addition of hindlimb suspension (OV-S). Also, neither of the two weight-bearing regimes (OV-SS and OV-SE) was able to attenuate the suspension-induced atrophy. In the vastus intermedius and vastus lateralis, however, OV-SS was able to partially retard the atrophy associated with suspension. In both the plantaris and vastus intermedius, only OV-SS was able to partially reverse the slow-to-fast isomyosin transitions associated with suspension. These results suggest that the type of mechanical activity is important in determining adaptation to altered loading conditions, with OV-SS appearing more effective than OV-SE in reversing the effects of unweighting.
This paper presents recent results from a mission architecture study of planetary aerial explorers. In this study, several mission scenarios were developed in simulation and evaluated on success in meeting mission goals. This aerial explorer mission architecture study is unique in comparison with previous Mars airplane research activities. The study examines how aerial vehicles can find and gain access to otherwise inaccessible terrain features of interest. The aerial explorer also engages in a high-level of (indirect) surface interaction, despite not typically being able to takeoff and land or to engage in multiple flights/sorties. To achieve this goal, a new mission paradigm is proposed: aerial explorers should be considered as an additional element in the overall Entry, Descent, Landing System (EDLS) process. Further, aerial vehicles should be considered primarily as carrier/utility platforms whose purpose is to deliver air-deployed sensors and robotic devices, or symbiotes, to those high-value terrain features of interest.
An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.
Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.
The increase in automated capabilities of small Uncrewed Aerial Systems (sUAS) has enabled the human operators to manage larger numbers of vehicles simultaneously. As this happens, the operational paradigm shifts to an m:N configuration where multiple operators (m) are managing multiple vehicles (N) together. However, many questions about how operators will interact with each other and share interaction across the vehicle pool are yet unanswered. Therefore, stakeholders from government and industry have partnered to develop ground control station concepts for such operations. The work presented in this paper aims to identify factors that contribute to operator workload. A supervised machine learning-based method built using Support Vector Machines and K-fold cross-validation was used to create workload prediction models for various NASA TLX subscales by leveraging features related to interactions and their relative timings during m:N operations. Results show that the models yielded fairly high predictive accuracies ranging from ~60-75%.
PandaX-4T and XENONnT have recently reported the first measurement of nuclear recoils induced by the B 8 solar neutrino flux, through the coherent elastic neutrino-nucleus scattering ( CE ν NS ) channel. As long anticipated, this is an important milestone for dark matter searches as well as for neutrino physics. This measurement means that these detectors have reached exposures such that searches for low mass, ≲ 10 GeV dark matter cannot be analyzed using the background-free paradigm going forward. It also opens a new era for these detectors to be used as neutrino observatories. In this paper we assess the sensitivity of these new measurements to new physics in the neutrino sector. We focus on neutrino nonstandard interactions (NSI) and show that—despite the still moderately low statistical significance of the signals—these data already provide valuable information. We find that limits on NSI from PandaX-4T and XENONnT measurements are comparable to those derived using combined COHERENT CsI and LAr data. Furthermore, they provide sensitivity to pure τ flavor parameters that are not accessible using stopped-pion or reactor sources. With larger exposures and consequently improvements of statistical uncertainties, forthcoming data from these experiments will provide important, novel results for CE ν NS -related physics. Published by the American Physical Society 2025
The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration system resulting from a NASA Jet Propulsion Laboratory (JPL) program of research into the application of graphical methods for rapidly accessing, displaying, and analyzing large multi variate multidisciplinary data sets. Running under UNIX it is an integrated multi-application executing environment using a data-linking paradigm to dynamically interconnect and control multiple windows containing a variety of displays and manipulators. This paradigm, resulting in a system similar to a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but leads to a highly intuitive, easy-to-learn user interface. It provides great flexibility in rapidly interacting with large masses of complex data to detect trends, correlations, and anomalies. The system, containing an expanding suite of non-domain-specific applications, provides for the ingestion of a variety of data base formats and hard -copy output of all displays. Remote networked workstations running LinkWinds may be interconnected, providing a multiuser science environment (MUSE) for collaborative data exploration by a distributed science team. The system is being developed in close collaboration with investigators in a variety of science disciplines using both archived and real-time data. It is currently being used to support the Microwave Limb Sounder (MLS) in orbit aboard the Upper Atmosphere Research Satellite (UARS). This paper describes the application of LinkWinds to this data to rapidly detect features, such as the ozone hole configuration, and to analyze correlations between chemical constituents of the atmosphere.
The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.
Expanding man's presence in space requires capable, dexterous robots capable of being controlled from the Earth. Traditional 'hand-in-glove' control paradigms require the human operator to directly control virtually every aspect of the robot's operation. While the human provides excellent judgment and perception, human interaction is limited by low bandwidth, delayed communications. These delays make 'hand-in-glove' operation from Earth impractical. In order to alleviate many of the problems inherent to remote operation, Stanford University's Aerospace Robotics Laboratory (ARL) has developed the Object-Based Task-Level Control architecture. Object-Based Task-Level Control (OBTLC) removes the burden of teleoperation from the human operator and enables execution of tasks not possible with current techniques. OBTLC is a hierarchical approach to control where the human operator is able to specify high-level, object-related tasks through an intuitive graphical user interface. Infrequent task-level command replace constant joystick operations, eliminating communications bandwidth and time delay problems. The details of robot control and task execution are handled entirely by the robot and computer control system. The ARL has implemented the OBTLC architecture on a set of Free-Flying Space Robots. The capability of the OBTLC architecture has been demonstrated by controlling the ARL Free-Flying Space Robots from NASA Ames Research Center.
The first phase of an effort to develop a NASA version of the Cybele software system has been completed. To give meaning to even a highly abbreviated summary of the modifications to be embodied in the NASA version, it is necessary to present the following background information on Cybele: Cybele is a proprietary software infrastructure for use by programmers in developing agent-based application programs [complex application programs that contain autonomous, interacting components (agents)]. Cybele provides support for event handling from multiple sources, multithreading, concurrency control, migration, and load balancing. A Cybele agent follows a programming paradigm, called activity-centric programming, that enables an abstraction over system-level thread mechanisms. Activity centric programming relieves application programmers of the complex tasks of thread management, concurrency control, and event management. In order to provide such functionality, activity-centric programming demands support of other layers of software. This concludes the background information. In the first phase of the present development, a new architecture for Cybele was defined. In this architecture, Cybele follows a modular service-based approach to coupling of the programming and service layers of software architecture. In a service-based approach, the functionalities supported by activity-centric programming are apportioned, according to their characteristics, among several groups called services. A well-defined interface among all such services serves as a path that facilitates the maintenance and enhancement of such services without adverse effect on the whole software framework. The activity-centric application-program interface (API) is part of a kernel. The kernel API calls the services by use of their published interface. This approach makes it possible for any application code written exclusively under the API to be portable for any configuration of Cybele.
Extended spaceflight under microgravity conditions leads to significant atrophy of weight-bearing muscles. Atrophy and hypertrophy are the extreme outcomes of the high degree of plasticity exhibited by skeletal muscle. Stimuli which control muscle plasticity include neuronal, hormonal, nutritional, and mechanical inputs. The mechanical stimulus for muscle is directly related to the work or exercise against a load performed. Little or no work is performed by weight-bearing muscles under microgravity conditions. A major hypothesis is that focal adhesion kinase (FAK) which is associated with integrin at the adherens junctions and costa meres of all skeletal muscles is an integral part of the major mechanism for molecular signaling upon mechanical stimulation in all muscle fibers. Additionally, we propose that myotonic protein kinase (DMPK) and dystrophin (DYSTR) also participate in distinct mechanically stimulated molecular signaling pathways that are most critical in type I and type II muscle fibers, respectively. To test these hypotheses, we will use the paradigms of hindlimb unloading and overloading in mice as models for microgravity conditions and a potential exercise countermeasure, respectively, in mice. We expect that FAK loss-of-function will impair hypertrophy and enhance atrophy in all skeletal muscle fibers whereas DYSTR and DMPK loss-of-function will have similar but more selective effects on Type IT and Type I fibers, respectively. Gene expression will be monitored by muscle-specific creatine kinase M promoter-reporter construct activity and specific MRNA and protein accumulation in the soleus (type I primarily) and plantaris (type 11 primarily) muscles. With these paradigms and assays, the following Specific Project Aims will be tested in genetically altered mice: 1) identify the roles of DYSTR and its pathway; 2) evaluate the roles of the DMPK and its pathway; 3) characterize the roles of FAK and its pathway and 4) genetically analyze the mechanisms and interactions between the FAK, DYSTR, and DMPK-associated pathways in single and specific combinations of mutants. The identification of potential signaling mechanisms may permit future development of pharmacological countermeasures for amelioration and prevention of the microgravity-induced atrophy in extended spaceflight, and the analysis of both overloading and unloading paradigms may provide further support for development of exercise-based countermeasures. Understanding the basic mechanisms of molecular signaling in muscle plasticity may aid our understanding and treatment of skeletal muscle atrophy not only in spaceflight but in similar problems of the aging population, in prolonged bed rest, and in cachexia associated with chronic disease.
During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult -- in both cost and schedule -- to enact. Indeed, the current capability-based paradigm that has emerged because of the constrained economic environment calls for the infusion of knowledge acquired during later design phases into earlier design phases, i.e. bring knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture as the need for more economically viable access to space solutions are needed in today's constrained economic environment. The problem of ascent trajectory optimization is not a new one. There are several programs that are widely used in industry that allows trajectory analysts to, based on detailed vehicle and insertion orbit parameters, determine the optimal ascent trajectory. Yet, little information is known about the launch vehicle early in the design phase - information that is required of many different disciplines in order to successfully optimize the ascent trajectory. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall Space Flight Center
In this paper we discuss the need for interactive factory schedule repair and improvement, and we identify case-based reasoning (CBR) as an appropriate methodology. Case-based reasoning is the problem solving paradigm that relies on a memory for past problem solving experiences (cases) to guide current problem solving. Cases similar to the current case are retrieved from the case memory, and similarities and differences of the current case to past cases are identified. Then a best case is selected, and its repair plan is adapted to fit the current problem description. If a repair solution fails, an explanation for the failure is stored along with the case in memory, so that the user can avoid repeating similar failures in the future. So far we have identified a number of repair strategies and tactics for factory scheduling and have implemented a part of our approach in a prototype system, called CABINS. As a future work, we are going to scale up CABINS to evaluate its usefulness in a real manufacturing environment.