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DOE OSTI2020

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization: Preprint

We discuss the value of collaborative, immersive visualization for the exploration of scientific datasets and review techniques and tools that have been developed and deployed at the National Renewable Energy Laboratory (NREL). We believe that collaborative visualizations linking statistical interfaces and graphics on laptops and high-performance computing (HPC) with 3D visualizations on immersive displays (head-mounted displays and large-scale immersive environments) enable scientific workflows that further rapid exploration of large, high-dimensional datasets by teams of analysts. We present a framework, PlottyVR, that blends statistical tools, general-purpose programming environments, and simulation with 3D visualizations. To contextualize this framework, we propose a categorization and loose taxonomy of collaborative visualization and analysis techniques. Finally, we describe how scientists and engineers have adopted this framework to investigate large, complex datasets.

collaborative visualization↗

DOE OSTI2021

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization

collaborative visualization↗

NASA NTRS2020

Biocene 2018

This 'minds-on' workshop will explore emerging cross-discipline tools and techniques for moving Bio-Inspired Design (BID) into “standard practice” in systems engineering and engineering design. Discussion will center on state-of-the-art in BID tools, emerging toolkits for engineering innovation, and industry best practices. The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals for fuel burn reduction 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 10 times or more the discovery, analysis and development of aerospace systems using artificial intelligence and natural systems.

Shyam, Vikram↗

NASA NTRS1996

New Interfaces to Web Documents and Services

This paper reports on investigations into how to extend capabilities of the Virtual Research Center (VRC) for NASA's Advanced Concepts Office. The work was performed as part of NASA's 1996 Summer Faculty Fellowship program, and involved research into and prototype development of software components that provide documents and services for the World Wide Web (WWW). The WWW has become a de-facto standard for sharing resources over the internet, primarily because web browsers are freely available for the most common hardware platforms and their operating systems. As a consequence of the popularity of the internet, tools, and techniques associated with web browsers are changing rapidly. New capabilities are offered by companies that support web browsers in order to achieve or remain a dominant participant in internet services. Because a goal of the VRC is to build an environment for NASA centers, universities, and industrial partners to share information associated with Advanced Concepts Office activities, the VRC tracks new techniques and services associated with the web in order to determine the their usefulness for distributed and collaborative engineering research activities. Most recently, Java has emerged as a new tool for providing internet services. Because the major web browser providers have decided to include Java in their software, investigations into Java were conducted this summer.

Carlisle, W. H.↗

NASA NTRSDate not supplied

Aerospace Cognitive Engineering Laboratory (ACELAB) Simulator for Electric Vertical Takeoff and Landing (eVOTL) Research and Development

A new generation of aerospace innovators are looking for ways to quickly and efficiently transport people in a safe and environmentally friendly manner. In the not-too-distant future, passengers and goods are expected to routinely fly aboard a new breed of cleaner, smarter air vehicles. This represents a new and significant challenge to the Federal Aviation Agency (FAA) which is responsible for aircraft certification, pilot licensing, operating approval and airspace integration. To help streamline this process, NASA has formulated its Advanced Air Mobility (AAM) project to provide research capabilities for development and evaluation of these new concepts and an environment where industry and regulators can work together to understand the requirements and work toward consensus standards for the new market. This paper will describe the development of the Aerospace Cognitive Engineering Lab Rapid Automation Test (ACELeRATE) simulator. ACELeRATE is an adaptable fixed-base aircraft simulator focused on the investigation of the performance and interaction of pilots and increasingly automated aircraft systems. ACELeRATE can be re-configured to support various simulation environments. The simulator includes a simple reconfigurable cockpit placed within a 10-foot spherical dome with a cluster of real-time image generators, high-resolution displays and highly realistic scenery with the surrounding digital terrain and required cultural area details (e.g., hangars, runways, ramp areas, taxiways, test range apparatus, buildings with designated rooftop landing areas, and other man-made 3D structures). This paper will also describe the various hardware and software tools employed in the ACELeRATE simulator, including engineering tools used by NASA for electric Vertical Takeoff and Landing (eVTOL) vehicle equations of motion, wind-model simulation in an urban environment, as well as the various modeling techniques and tools used to quickly generate highly realistic 3D terrain models for low level flight including urban terrain and obstacle depictions.

AAM Simulation Cockpit↗

NASA NTRS1998

Scale in Remote Sensing and GIS: An Advancement in Methods Towards a Science of Scale

The term "scale", both in space and time, is central to remote sensing and Geographic Information Systems (GIS). The emergence and widespread use of GIS technologies, including remote sensing, has generated significant interest in addressing scale as a generic topic, and in the development and implementation of techniques for dealing explicitly with the vicissitudes of scale as a multidisciplinary issue. As science becomes more complex and utilizes databases that are capable of performing complex space-time data analyses, it becomes paramount that we develop the tools and techniques needed to operate at multiple scales, to work with data whose scales are not necessarily ideal, and to produce results that can be aggregated or disaggregated ways that suit the decision-making process. Contemporary science is constantly coping with compromises, and the data available for a particular study rarely fit perfectly with the scales at which the processes being investigated operate, or the scales that policy-makers require to make sound, rational decisions. This presentation discusses some of the problems associated with scale as related to remote sensing and GIS, and describes some of the questions that need to be addressed in approaching the development of a multidisciplinary "science of scale". Techniques for dealing with multiple scaled data that have been developed or explored recently are described as a means for recognizing scale as a generic issue, along with associated theory and tools that can be of simultaneous value to a large number of disciplines. These can be used to seek answers to a host of interrelated questions in the interest of providing a formal structure for the management and manipulation of scale and its universality as a key concept from a multidisciplinary perspective.

Quattrochi, D. A.↗

NASA NTRS1998

Scale in Remote Sensing and GIS: An Advancement in Methods Towards a Science of Scale

The term "scale", both in space and time, is central to remote sensing and geographic information systems (GIS). The emergence and widespread use of GIS technologies, including remote sensing, has generated significant interest in addressing scale as a generic topic, and in the development and implementation of techniques for dealing explicitly with the vicissitudes of scale as a multidisciplinary issue. As science becomes more complex and utilizes databases that are capable of performing complex space-time data analyses, it becomes paramount that we develop the tools and techniques needed to operate at multiple scales, to work with data whose scales are not necessarily ideal, and to produce results that can be aggregated or disaggregated in ways that suit the decision-making process. Contemporary science is constantly coping with compromises, and the data available for a particular study rarely fit perfectly with the scales at which the processes being investigated operate, or the scales that policy-makers require to make sound, rational decisions. This presentation discusses some of the problems associated with scale as related to remote sensing and GIS, and describes some of the questions that need to be addressed in approaching the development of a multidisciplinary "science of scale". Techniques for dealing with multiple scaled data that have been developed or explored recently are described as a means for recognizing scale as a generic issue, along with associated theory and tools that can be of simultaneous value to a large number of disciplines. These can be used to seek answers to a host of interrelated questions in the interest of providing a formal structure for the management and manipulation of scale and its universality as a key concept from a multidisciplinary perspective.

Quattrochi, Dale A.↗

NASA NTRS1990

Visualization of fluid dynamics at NASA Ames

Some of the hardware and software tools and techniques in use at NASA's numerical aerodynamic simulation facility for the analysis of computational fluid dynamics are described. The visualization process can be illustrated by video tapes and stereo pictures. Although these visualization tools have dramatically improved the ability to conduct research in fluid dynamics, a comparison of the current environment for analysis with an 'ideal' environment illustrates that there are still major improvements that should be made. The most time-consuming task in future analyses of the increasingly complex computer simulations will be the extraction and clear display of the key features. In addition, the interface between the workstation and the scientist should be improved significantly. Current research on techniques for creating these improvements is described.

Watson, V.↗

NASA NTRS1981

Use of software tools in the development of real time software systems

The transformation of a preexisting software system into a larger and more versatile system with different mission requirements is discussed. The history of this transformation is used to illustrate the use of structured real time programming techniques and tools to produce maintainable and somewhat transportable systems. The predecessor system is a single ground diagnostic system; its purpose is to exercise a computer controlled hardware set prior to its deployment in its functional environment, as well as test the equipment set by supplying certain well known stimulas. The successor system (FTE) is required to perform certain testing and control functions while this hardware set is in its functional environment. Both systems must deal with heavy user input/output loads and a new I/O requirement is included in the design of the FTF system. Human factors are enhanced by adding an improved console interface and special function keyboard handler. The additional features require the inclusion of much new software to the original set from which FTF was developed. As a result, it is necessary to split the system into a duel programming configuration with high rates of interground communications. A generalized information routing mechanism is used to support this configuration.

Garvey, R. C.↗

NASA NTRS1991

Integrated trajectory and control analysis for generic hypersonic vehicles

A tool which supports integrated assessment of air-breathing hypersonic vehicle trajectory management and control strategy has been developed by Hattis and Malchow (1991). Using a two-point boundary value problem solution technique, the tool can construct an entire near-minimum-fuel trajectory and desired control strategy from takeoff to orbit, while satisfying physically derived inequality constraints and while achieving efficient propulsive mode phasing. A strategy is also formulated to construct preliminary trajectory and control history representations with less computational burden than required for the overall flight profile assessment. A tabulated example hypersonic vehicle model has been used to demonstrate the integrated analysis methodology. To assure good numerical behavior when the algorithm uses tabulated model data, a multidimensional cubic spline curve smoothing routine has been developed. A dynamic-pressure-constrained, near-fuel-optimal trajectory was computed to provide examples of information that the methodology can provide. Previously unspecified propulsive discontinuities were located, flight regimes demanding rapid attitude changes were identified, available and closed-loop controller authority was ascertained, and inadequacies in vehicle and specific subsystem model representations were determined.

Hattis, Philip D.↗

NASA NTRS1995

Supersonic civil airplane study and design: Performance and sonic boom

Since aircraft configuration plays an important role in aerodynamic performance and sonic boom shape, the configuration of the next generation supersonic civil transport has to be tailored to meet high aerodynamic performance and low sonic boom requirements. Computational fluid dynamics (CFD) can be used to design airplanes to meet these dual objectives. The work and results in this report are used to support NASA's High Speed Research Program (HSRP). CFD tools and techniques have been developed for general usages of sonic boom propagation study and aerodynamic design. Parallel to the research effort on sonic boom extrapolation, CFD flow solvers have been coupled with a numeric optimization tool to form a design package for aircraft configuration. This CFD optimization package has been applied to configuration design on a low-boom concept and an oblique all-wing concept. A nonlinear unconstrained optimizer for Parallel Virtual Machine has been developed for aerodynamic design and study.

Cheung, Samson↗

DOE OSTI2021

Diolkos: Improving ethernet throughput through dynamic port selection

In large networked systems, a sudden increase in traffic could slowdown the network significantly, impacting network quality for multiple users. We present Diolkos, a system that leverages smart switches to dynamically re-reroute data flows in response to drops in performance. In contrast to other techniques, our tool predicts the future throughput at each port in a switch if a data flow were to be sent through it, and updates which port should be taken to maximize throughput. We use several techniques to predict network switch performance on a software defined network (SDN) mimicking topologies commonly found in datacenters. Experimentally, we demonstrate the effectiveness of choosing a port to send flows through based on predicted performance. We found that using a distributed predictive technique achieves a 24% improvement over using a traditional heuristic technique.

port selection, performance enhancement, Neural Ne↗

NASA NTRS2012

Can Terrestrial Microbes Grow on Mars?

The theme for AbSciCon 2012 is "Exploring Life: Past and Present, Near and Far." The conference will address our current understanding of life - from processes at the molecular level to those which operate at planetary scales. Studying these aspects of life on Earth provides an essential platform from which to examine the potential for life on other worlds, both within our solar system and beyond. Mars exhibits a variety of extreme environments characterized by high UV and ionizing radiation flux, low pressure anoxic atmosphere, scarce or absent liquid water, extreme low temperatures, etc. The ability of terrestrial microorganisms to survive and adapt to the Mars environment has profound implications for astrobiology, planetary protection, and Mars life detection missions. At the NASA Ames Synthetic Biology Initiative, we believe that synthetic biology has the potential to revolutionize human space exploration. As such, the initiative is dedicated to applying the tools and techniques of synthetic biology to space exploration and astrobiology. Biological solutions will be invaluable for space exploration because they are not resource intensive, and they are versatile and self-renewing. An understanding of how to work with DNA in an unfavorable environment is paramount to utilizing biological tools on space missions. Furthermore, the ability to adjust life to the parameters of Mars is vital both to discovering what life on Mars might look like, and to using biological tools under such conditions. As a first step, we need an energy-efficient, low cost means of transporting, storing, and protecting genomic DNA, DNA parts, and whole microbial strains. Our goal is to develop and demonstrate viable and superior alternatives to standard DNA storage methods, which can be optimized to the conditions of space exploration, using synthetic biology as a tool. This includes protocols and kit designs for easy and repeatable DNA and strain recovery from protective storage conditions. We are constructing newly engineered genetic parts for different valuable host organisms, designed to increased long-term survival and functional retention. These methods should be applied for DNA and strain storage and transportation. In parallel, we seek inspiration from natural organisms that have developed means for survival in extreme environmental conditions. We are utilizing novel techniques for analysis of lipid biomarkers in the Antarctic Dry Valleys in order to identify resident microbes in the Antarctic soil and permafrost, as well as biomarker fossils of organisms that survived in the valleys in ages past. Through the identification of these life forms, we hope to understand and draw on new biological tools and strategies for synthetic biological applications on Mars.

Rothschild, Lynn↗

NASA NTRS2010

Orion FSW V and V and Kedalion Engineering Lab Insight

NASA, along with its prime Orion contractor and its subcontractor s are adapting an avionics system paradigm borrowed from the manned commercial aircraft industry for use in manned space flight systems. Integrated Modular Avionics (IMA) techniques have been proven as a robust avionics solution for manned commercial aircraft (B737/777/787, MD 10/90). This presentation will outline current approaches to adapt IMA, along with its heritage FSW V&V paradigms, into NASA's manned space flight program for Orion. NASA's Kedalion engineering analysis lab is on the forefront of validating many of these contemporary IMA based techniques. Kedalion has already validated many of the proposed Orion FSW V&V paradigms using Orion's precursory Flight Test Article (FTA) Pad Abort 1 (PA-1) program. The Kedalion lab will evolve its architectures, tools, and techniques in parallel with the evolving Orion program.

Mangieri, Mark L.↗

DOE OSTI2020

Cognition at the Point of Sensing

Over the last 15 years, compressive sensing techniques have been developed which have the potential to greatly reduce the amount of data collected by systems while preserving the amount of information obtained. A cost of this efficiency is that a computationally-intensive optimization routine must be used to put the sensed data into a form that a person can interpret. At the same time, machine learning techniques have experienced tremendous growth as well. Machines have demonstrated the ability learn how to effectively perform tasks such as detection and classification at speeds much faster than humanly possible. Our goal in this project was to study the feasibility of using compressive sensing systems "at the edge." That is, how can compressive sensing sensors be deployed such that information is created at the remote sensor rather than sending raw data to a central processing location? Studies were performed to analyze whether machine learning could be done on the compressively sensed data in its raw form. If a machine is performing the task, is it possible to do so without putting the data into a human interpretable form? We show that this is possible for some systems, in particular a compressive sensing snapshot imaging spectrometer. Machine learning tasks were demonstrated to be more effective and more robust to noise when the machine learning algorithm worked on data in its raw form. This system is shown to outperform a traditional spectrometer. Techniques for reducing the complexity of the reconstruction routine were also analyzed. Techniques for such as data regularization, deep neural networks, and matrix completion were studied and shown to have benefits over traditional reconstruction techniques. In this project we showed that compressive sensing sensors are indeed feasible at the edge. As always, sensors and algorithms must be carefully tuned to work in the constrained environment. In this project we developed tools and techniques to enable those analyses.

47 OTHER INSTRUMENTATION↗

NASA NTRS1990

Closed-form solution of decomposable stochastic models

Markov and semi-Markov processes are increasingly being used in the modeling of complex reconfigurable systems (fault tolerant computers). The estimation of the reliability (or some measure of performance) of the system reduces to solving the process for its state probabilities. Such a model may exhibit numerous states and complicated transition distributions, contributing to an expensive and numerically delicate solution procedure. Thus, when a system exhibits a decomposition property, either structurally (autonomous subsystems), or behaviorally (component failure versus reconfiguration), it is desirable to exploit this decomposition in the reliability calculation. In interesting cases there can be failure states which arise from non-failure states of the subsystems. Equations are presented which allow the computation of failure probabilities of the total (combined) model without requiring a complete solution of the combined model. This material is presented within the context of closed-form functional representation of probabilities as utilized in the Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE) tool. The techniques adopted enable one to compute such probability functions for a much wider class of systems at a reduced computational cost. Several examples show how the method is used, especially in enhancing the versatility of the SHARPE tool.

Sjogren, Jon A.↗

DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1997

A Categorization of Dynamic Analyzers

Program analysis techniques and tools are essential to the development process because of the support they provide in detecting errors and deficiencies at different phases of development. The types of information rendered through analysis includes the following: statistical measurements of code, type checks, dataflow analysis, consistency checks, test data,verification of code, and debugging information. Analyzers can be broken into two major categories: dynamic and static. Static analyzers examine programs with respect to syntax errors and structural properties., This includes gathering statistical information on program content, such as the number of lines of executable code, source lines. and cyclomatic complexity. In addition, static analyzers provide the ability to check for the consistency of programs with respect to variables. Dynamic analyzers in contrast are dependent on input and the execution of a program providing the ability to find errors that cannot be detected through the use of static analysis alone. Dynamic analysis provides information on the behavior of a program rather than on the syntax. Both types of analysis detect errors in a program, but dynamic analyzers accomplish this through run-time behavior. This paper focuses on the following broad classification of dynamic analyzers: 1) Metrics; 2) Models; and 3) Monitors. Metrics are those analyzers that provide measurement. The next category, models, captures those analyzers that present the state of the program to the user at specified points in time. The last category, monitors, checks specified code based on some criteria. The paper discusses each classification and the techniques that are included under them. In addition, the role of each technique in the software life cycle is discussed. Familiarization with the tools that measure, model and monitor programs provides a framework for understanding the program's dynamic behavior from different, perspectives through analysis of the input/output data.

Lujan, Michelle R.↗