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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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DOE OSTI2013

2013 Progress Report -- DOE Joint Genome Institute

In October 2012, we introduced a 10-Year Strategic Vision [http://bit.ly/JGI-Vision] for the Institute. A central focus of this Strategic Vision is to bridge the gap between sequenced genomes and an understanding of biological functions at the organism and ecosystem level. This involves the continued massive-scale generation of sequence data, complemented by orthogonal new capabilities to functionally annotate these large sequence data sets. Our Strategic Vision lays out a path to guide our decisions and ensure that the evolving set of experimental and computational capabilities available to DOE JGI users will continue to enable groundbreaking science.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

NREL: Working Towards a Superlab 2.0 With ESnet and Other National Laboratories

We can currently link models and simulations across the national laboratory complex, but imagine connecting these models with equipment, devices, and scientists so they can work together as if side by side instead of thousands of miles apart. In a future like this, researchers could run experiments that leverage thousands of devices to model the millions of devices that make up our increasingly complex energy systems. With such resources, labs could simulate, for example, the electric grid of California and validate control strategies to best serve critical loads during outages caused by wildfires. The National Renewable Energy Laboratory's (NREL's) Advanced Research on Integrated Energy Systems (ARIES) platform is making that vision a reality, one step at a time.

ARIES↗
NASA NTRS1987

Real time AI expert system for robotic applications

A computer controlled multi-robot process cell to demonstrate advanced technologies for the demilitarization of obsolete chemical munitions was developed. The methods through which the vision system and other sensory inputs were used by the artificial intelligence to provide the information required to direct the robots to complete the desired task are discussed. The mechanisms that the expert system uses to solve problems (goals), the different rule data base, and the methods for adapting this control system to any device that can be controlled or programmed through a high level computer interface are discussed.

Follin, John F.↗
DOE OSTI2021

Toward a Seamless Integration of Computing, Experimental, and Observational Science Facilities: A Blueprint to Accelerate Discovery

The Department of Energy, Office of Science operates world-leading facilities for experimental, observational, and computational science. DOE supercomputing facilities will reach performance at the scale of ExaFLOPs in the coming years, enabling new vistas of scale and precision for large scale simulations and data analysis. Experimental scientific facilities are undergoing similar upgrades that will lead to higher data rates and correspondingly larger computational demands, and will increase the need for near-real-time processing and resilient support for more complex workflows. A transformation of science is underway, with workloads at supercomputing facilities increasingly driven by this explosion of data from instruments and experimental facilities, as well as the accelerating use of Artificial Intelligence (AI) as a tool for scientific discovery. A seamless integration of computing, networking, instruments, and experimental facilities is required to support these emerging workloads and open up a new frontier of U.S. leadership in scientific discovery. We propose to accomplish this by providing frictionless access to the ASCR supercomputing facilities. We describe our vision of combining the power of ASCR supercomputers and networking infrastructure into an integrated scalable fabric, available to end user scientists via interfaces that aim to automate and simplify access to high performance computing systems. This will enable unprecedented computational science capabilities for experimental and observational facilities, and will create new opportunities to combine large simulations and modeling with experimental facility data analysis. This blueprint for creating an integrated network of computational and experimental facilities will provide an enriched discovery environment and open doors for new scientific communities to access the DOE’s world-leading computing and networking capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Can Effective Synthetic Vision System Displays be Implemented on Limited Size Display Spaces?

The Synthetic Vision Systems (SVS) element of the NASA Aviation Safety Program is striving to eliminate poor visibility as a causal factor in aircraft accidents, and to enhance operational capabilities of all types or aircraft. To accomplish these safety and situation awareness improvements, the SVS concepts are designed to provide a clear view of the world ahead through the display of computer generated imagery derived from an onboard database of terrain, obstacle and airport information. An important issue for the SVS concept is whether useful and effective Synthetic Vision System (SVS) displays can be implemented on limited size display spaces as would be required to implement this technology on older aircraft with physically smaller instrument spaces. In this study, prototype SVS displays were put on the following display sizes: (a) size "A' (e.g. 757 EADI), (b) form factor "D" (e.g. 777 PFD), and (c) new size "X" (Rectangular flat-panel, approximately 20 x 25 cm). Testing was conducted in a high-resolution graphics simulation facility at NASA Langley Research Center. Specific issues under test included the display size as noted above, the field-of-view (FOV) to be shown on the display and directly related to FOV is the degree of minification of the displayed image or picture. Using simulated approaches with display size and FOV conditions held constant no significant differences by these factors were found. Preferred FOV based on performance was determined by using approaches during which pilots could select FOV. Mean preference ratings for FOV were in the following order: (1) 30 deg., (2) Unity, (3) 60 deg., and (4) 90 deg., and held true for all display sizes tested. Limitations of the present study and future research directions are discussed.

Comstock, J. Raymond, Jr.↗
DOE OSTI2019

A Logical Model of Homology for Comparative Biology

There is a growing body of research on the evolution of anatomy in a wide variety of organisms. Discoveries in this field could be greatly accelerated by computational methods and resources that enable these findings to be compared across different studies and different organisms and linked with the genes responsible for anatomical modifications. Homology is a key concept in comparative anatomy; two important types are historical homology (the similarity of organisms due to common ancestry) and serial homology (the similarity of repeated structures within an organism). We explored how to most effectively represent historical and serial homology across anatomical structures to facilitate computational reasoning. We assembled a collection of homology assertions from the literature with a set of taxon phenotypes for the skeletal elements of vertebrate fins and limbs from the Phenoscape Knowledgebase. Using seven competency questions, we evaluated the reasoning ramifications of two logical models: the Reciprocal Existential Axioms (REA) homology model and the Ancestral Value Axioms (AVA) homology model. The AVA model returned all user-expected results in addition to the search term and any of its subclasses. The AVA model also returns any superclass of the query term in which a homology relationship has been asserted. The REA model returned the user-expected results for five out of seven queries. We identify some challenges of implementing complete homology queries due to limitations of OWL reasoning. This work lays the foundation for homology reasoning to be incorporated into other ontology-based tools, such as those that enable synthetic supermatrix construction and candidate gene discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Abstract Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Workflows Community Summit: Tightening the Integration between Computing Facilities and Scientific Workflows

Scientific workflows are used almost universally across science domains for solving complex and largescale computing and data analysis problems. The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and thus must execute on a range of large-scale computer systems, from local clusters to public clouds and upcoming exascale HPC platforms. Managing these executions is often a significant undertaking, requiring a sophisticated and versatile software infrastructure. Historically, infrastructures for workflow execution consisted of complex, integrated systems, developed in-house by workflow practitioners with strong dependencies on a range of legacy technologies—even including sets of ad hoc scripts. Due to the increasing need to support workflows, dedicated workflow systems were developed to provide abstractions for creating, executing, and adapting workflows conveniently and efficiently while ensuring portability. While these efforts are all worthwhile individually, there are now hundreds of independent workflow systems. These workflow systems are created and used by thousands of researchers and developers, leading to a rapidly growing corpus of workflows research publications. The resulting workflow system technology landscape is fragmented, which may present significant barriers for future workflow users due to many seemingly comparable, yet usually mutually incompatible, systems that exist. In order to tackle some of the challenges described above, the DOE-funded ExaWorks and NSF-funded WorkflowsRI projects have organized in 2021 a series of events entitled the “Workflows Community Summit”. The third edition of the “Workflows Community Summit” explored workflows challenges and opportunities from the perspective of computing centers and facilities. This third summit builds on two prior summits (https://workflowsri.org/summits) that (i) established a high level vision for workflows research; and (ii) explored technical approaches for realizing that vision. The third summit brought together a small group of facilities representatives with the aim to understand how workflows are currently being used at each facility, how facilities would like to interact with workflow developers and users, how workflows fit with facility roadmaps, and what opportunities there are for tighter integration between facilities and workflows. This report documents and organizes the wealth of information provided by the participants before, during, and after the summit.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Technologies Render Views of Earth for Virtual Navigation

On a December night in 1995, 159 passengers and crewmembers died when American Airlines Flight 965 flew into the side of a mountain while in route to Cali, Colombia. A key factor in the tragedy: The pilots had lost situational awareness in the dark, unfamiliar terrain. They had no idea the plane was approaching a mountain until the ground proximity warning system sounded an alarm only seconds before impact. The accident was of the kind most common at the time CFIT, or controlled flight into terrain says Trey Arthur, research aerospace engineer in the Crew Systems and Aviation Operations Branch at NASA s Langley Research Center. In situations such as bad weather, fog, or nighttime flights, pilots would rely on airspeed, altitude, and other readings to get an accurate sense of location. Miscalculations and rapidly changing conditions could contribute to a fully functioning, in-control airplane flying into the ground. To improve aviation safety by enhancing pilots situational awareness even in poor visibility, NASA began exploring the possibilities of synthetic vision creating a graphical display of the outside terrain on a screen inside the cockpit. How do you display a mountain in the cockpit? You have to have a graphics-powered computer, a terrain database you can render, and an accurate navigation solution, says Arthur. In the mid-1990s, developing GPS technology offered a means for determining an aircraft s position in space with high accuracy, Arthur explains. As the necessary technologies to enable synthetic vision emerged, NASA turned to an industry partner to develop the terrain graphical engine and database for creating the virtual rendering of the outside environment.

Source record↗
NASA NTRS1992

Algorithm For Simplified Robotic Tracking Of Weld Seams

Algorithm computes small cross-seam corrections to programmed path of welding robot. Intended for use with add-on vision system loosely coupled to robot, transmitting small amount of information about weld seam ahead of torch. Position of welding torch in reference frame of moving window estimated on basis of data on weld seam and speed of torch. Does not need data on position of torch, and does not transform data on seam to another reference frame.

Gutow, David A.↗
NASA NTRS1993

Robotic Tube-Gap Inspector

Robotic vision system measures small gaps between nearly parallel tubes. Robot-held video camera examines closely spaced tubes while computer determines gaps between tubes. Video monitor simultaneously displays data on gaps.

Gilbert, Jeffrey L.↗
NASA NTRS1992

Visualization and modeling of factors influencing visibility in computer-aided crewstation design

We have developed two modules for use in computer-aided design (CAD) of crewstation environments that enhance the designer's appreciation of factors influencing the pilot's vision and visual processing capacity. The Binocular Optics Module (BOM) is an interactive tool for visualizing geometric aspects of (1) how retinal imagery of the environment changes on the pilot's retinas under conditions of eye and object motion, and (2) how visual capabilities that can be modeled as regions or contours on the retinas, affect spatial perception of the environment. The Visual Performance Module (VPM) contains a signal processing model of human visual discrimination that quantitatively predicts visual discrimination performance. The outputs of the VPM are retinal contours that represent performance probabilities. These contours may be used as inputs to the BOM for visualizing those volumes of space within the crewstation that bound different levels of the pilot's of visual discrimination capability. Used together, the BOM and VPM provide the designer with the opportunity to interactively explore relationships between environmental retinal imagery and visual function, and the ability to factor the pilot's visual capabilities into the earliest phases of crewstation CAD.

Arditi, Aries↗
NASA NTRS2002

Terrain Portrayal for Head-Down Displays Experiment

The General Aviation Element of the Aviation Safety Program's Synthetic Vision Systems (SVS) Project is developing technology to eliminate low visibility induced General Aviation (GA) accidents. SVS displays present computer generated 3-dimensional imagery of the surrounding terrain on the Primary Flight Display (PFD) to greatly enhance pilot's situation awareness (SA), reducing or eliminating Controlled Flight into Terrain, as well as Low-Visibility Loss of Control accidents. SVS-conducted research is facilitating development of display concepts that provide the pilot with an unobstructed view of the outside terrain, regardless of weather conditions and time of day. A critical component of SVS displays is the appropriate presentation of terrain to the pilot. An experimental study has been conducted at NASA Langley Research Center (LaRC) to explore and quantify the relationship between the realism of the terrain presentation and resulting enhancements of pilot SA and pilot performance. Composed of complementary simulation and flight test efforts, Terrain Portrayal for Head-Down Displays (TP-HDD) experiments will help researchers evaluate critical terrain portrayal concepts. The experimental effort is to provide data to enable design trades that optimize SVS applications, as well as develop requirements and recommendations to facilitate the certification process. This paper focuses on the experimental set-up and preliminary qualitative results of the TP-HDD simulation experiment. In this experiment a fixed based flight simulator was equipped with various types of Head Down flight displays, ranging from conventional round dials (typical of most GA aircraft) to glass cockpit style PFD's. The variations of the PFD included an assortment of texturing and Digital Elevation Model (DEM) resolution combinations. A test matrix of 10 terrain display configurations (in addition to the baseline displays) were evaluated by 27 pilots of various backgrounds and experience levels. Qualitative (questionnaires) and quantitative (pilot performance and physiological) data were collected during the experimental runs. Preliminary results indicate that all of the evaluation pilots favored SVS displays over standard gauges, in terms of terrain awareness, SA, and perceived pilot performance. Among the terrain portrayal concepts tested, most pilots preferred the higher-resolution DEM. In addition, with minimal training, low-hour VFR evaluation pilots were able to negotiate a precision approach using SVS displays with a tunnel in the sky guidance concept.

Hughes, Monica F.↗
NASA NTRS2004

Format for Interchange and Display of 3D Terrain Data

Visible Scalable Terrain (ViSTa) is a software format for production, interchange, and display of three-dimensional (3D) terrain data acquired by stereoscopic cameras of robotic vision systems. ViSTa is designed to support scalability of data, accuracy of displayed terrain images, and optimal utilization of computational resources. In a ViSTa file, an area of terrain is represented, at one or more levels of detail, by coordinates of isolated points and/or vertices of triangles derived from a texture map that, in turn, is derived from original terrain images. Unlike prior terrain-image software formats, ViSTa includes provisions to ensure accuracy of texture coordinates. Whereas many such formats are based on 2.5-dimensional terrain models and impose additional regularity constraints on data, ViSTa is based on a 3D model without regularity constraints. Whereas many prior formats require external data for specifying image-data coordinate systems, ViSTa provides for the inclusion of coordinate-system data within data files. ViSTa admits highspeed loading and display within a Java program. ViSTa is designed to minimize file sizes and maximize compressibility and to support straightforward reduction of resolution to reduce file size for Internet-based distribution.

Backes, Paul↗
NASA NTRS2003

Improved Collision-Detection Method for Robotic Manipulator

An improved method has been devised for the computational prediction of a collision between (1) a robotic manipulator and (2) another part of the robot or an external object in the vicinity of the robot. The method is intended to be used to test commanded manipulator trajectories in advance so that execution of the commands can be stopped before damage is done. The method involves utilization of both (1) mathematical models of the robot and its environment constructed manually prior to operation and (2) similar models constructed automatically from sensory data acquired during operation. The representation of objects in this method is simpler and more efficient (with respect to both computation time and computer memory), relative to the representations used in most prior methods. The present method was developed especially for use on a robotic land vehicle (rover) equipped with a manipulator arm and a vision system that includes stereoscopic electronic cameras. In this method, objects are represented and collisions detected by use of a previously developed technique known in the art as the method of oriented bounding boxes (OBBs). As the name of this technique indicates, an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs), as in the example of Figure 1. Unlike prior methods, the OBB/OBP method does not require any divisions or transcendental functions; this feature leads to greater robustness and numerical accuracy. The OBB/OBP method was selected for incorporation into the present method because it offers the best compromise between accuracy on the one hand and computational efficiency (and thus computational speed) on the other hand.

Leger, Chris↗
NASA NTRS2015

Physiological Health Challenges for Human Missions to Mars

During the next decades, manned space missions are expected to be aiming at the Lagrange points, near Earth asteroids, and Mars flyby and/or landing. The question is therefore: Are we ready to go? To answer this with a yes, we are currently using the International Space Station to develop an integrated human physiological countermeasure suite. The integrated countermeasure suite will most likely encounter: 1) Exercise devices for aerobic, dynamic and resistive exercise training; 2) sensory‐motor computer training programs and anti‐motion sickness medication for preparing EVAs and G‐transitions; 3) lower limb bracelets for preventing and/or treating the VIIP (vision impairment and intracranial pressure) syndrome; 4) nutritional components for maintenance of bone, muscle, the cardiovascular system and preventing oxidative stress and damage and immune deficiencies (e. g. omega‐3 fatty acids, PRO/K, anti‐oxidants and less salt and iron); 5) bisphosphonates for preventing bone degradation.; 6) lower body compression garment and oral salt and fluid loading for landing on a planetary surface to combat orthostatic intolerance; 7) laboratory analysis equipment for individualized monitoring of biomarkers in blood, urine and saliva for estimation of health status in; 8) advanced ultrasound techniques for monitoring bone and cardiovascular health; and 9) computer modeling programs for individual health status assessments of efficiency and subsequent adjustments of countermeasures. In particular for future missions into deep space, we are concerned with the synergistic effects of weightlessness, radiation, operational constraints and other spaceflight environmental factors. Therefore, increased collaboration between physiological, behavioral, radiation and space vehicle design disciplines are strongly warranted. Another venue we are exploring in NASA's Human Research Program is the usefulness of artificial gravity for mitigating the health risks of long duration weightlessness.

Norsk, Peter↗
DOE OSTI2018

Future Online Analysis Platform Workshop Report

Recent technology trends, such as the increasing focus on data management technologies and the emergence of sustainable on-demand computing and commercial cloud facilities provide initial steps and potential building blocks for creating such a compute facility. How do we fill the gap between what we have now and the capabilities we need to make the vision of an online data facility a reality? What research challenges need to be addressed – and can be addressed – in the coming 5-10 years? How should we adjust our vision if they are not solved? Is such a facility compatible with the existing and evolving exascale resources and/or how should they evolve to be compatible? How do “beyond Moore’s law” technologies enable advanced data analysis? Those are the challeges that the Future Platform workshop was organized to address. This report is organized as follows. Section 2 summarizes data challenges and patterns related to the exemplar use cases presented during the first half day of the workshop. Section 3 summarizes the requirements presented by those use cases as well as a synthesis of those requirements into a Future Platform definition achieved on the 3rd half day of the workshop (morning of the 2nd day). Section 4 includes area breakout reports from the areas on the 2nd half day of the workshop (afternoon of the 1st day). Finally Section 5 has a report on recommendation for building methodology and metrics. The report concludes in Section 6.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Probabilistic Neural Computing with Stochastic Devices

Abstract The brain has effectively proven a powerful inspiration for the development of computing architectures in which processing is tightly integrated with memory, communication is event‐driven, and analog computation can be performed at scale. These neuromorphic systems increasingly show an ability to improve the efficiency and speed of scientific computing and artificial intelligence applications. Herein, it is proposed that the brain's ubiquitous stochasticity represents an additional source of inspiration for expanding the reach of neuromorphic computing to probabilistic applications. To date, many efforts exploring probabilistic computing have focused primarily on one scale of the microelectronics stack, such as implementing probabilistic algorithms on deterministic hardware or developing probabilistic devices and circuits with the expectation that they will be leveraged by eventual probabilistic architectures. A co‐design vision is described by which large numbers of devices, such as magnetic tunnel junctions and tunnel diodes, can be operated in a stochastic regime and incorporated into a scalable neuromorphic architecture that can impact a number of probabilistic computing applications, such as Monte Carlo simulations and Bayesian neural networks. Finally, a framework is presented to categorize increasingly advanced hardware‐based probabilistic computing technologies.

Misra, Shashank↗