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Special drum for a computer-controlled printer improves density trace of scientific data. The drum provides uniformly shaped characters and evenly spaced variations of print density that precisely reflect data magnitude. This device plots temperature profiles, geographic contours, pressure gradients, electric potential gradients, and magnetic field configurations.
The use of metric tensors as inputs to computer programs designed to formulate engineering and scientific problems is considered as an alternative to the use of coordinate transformation equations.
The fundamental principles of the operation of a coastal coordinating and computing center under conditions of automation are presented. Special attention is devoted to the work of Coastal Computer Center of the Arctic and Antarctic Scientific Research Institute. This center generalizes from data collected in expeditions and also from observations made at polar stations.
Specific numerical results for the squaring loss in Costas loop tracking are discussed for cases when the input data were biphase-L, and the Costas loop arm filters were of the n-pole Butterworth type. It is pointed out that a simple scientific calculator may be used for the computations, provided the transfer function of the arm filter has simple poles. The technique can also be used to compute the squaring loss in other modulation forms, such as unbalanced quadriphase-shift-keying (QPSK).
Facilities and capabilities for disseminating imagery and other information are described as well as the computer center and production services offered. The scientific staff, visitor program, projects, conferences, publications, and communications are also discussed. Support for the Ames Vertical gun facility and the responsibilities of the Lunar and Planetary Science Council are summarized.
Many of the models now used in science and engineering are over a century old. And most of them can be implemented on modern digital computers only with considerable difficulty. Some new basic models are discussed which are much more directly suitable for digital computer simulation. The fundamental principle is that the models considered herein are as suitable as possible for implementation on digital computers. It is then a matter of scientific analysis to determine whether such models can reproduce the behavior seen in physical and other systems. Such analysis was carried out in several cases, and the results are very encouraging.
Principal Investigator (PI) in a box is a computer system designed to help optimize the scientific results of experiments that are performed in space. The system will assist the astronaut experimenters in the collection and analysis of experimental data, recognition and pursuit of 'interesting' results, optimal use of the time allocated to the experiment, and troubleshooting of the experiment apparatus. This document discusses the problems that motivate development of 'PI-in-a-box', and presents a high- level system overview and a detailed description of each of the modules that comprise the current version of the system.
Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.
While the advent of distributed and grid computing systems will open new opportunities for scientific exploration, the reality of such implementations could prove to be a system administrator's nightmare. A lot of effort is being spent on identifying and resolving the obvious problems of security, scheduling, authentication and authorization. Lurking in the background, though, are the largely unaddressed issues of accountability and usage accounting: (1) mapping resource usage to resource users; (2) defining usage economies or methods for resource exchange; (3) describing implementation standards that minimize and compartmentalize the tasks required for a site to participate in a grid.
Grid technology is the up and coming technology that is enabling widely disparate services to be offered to users that is very economical, easy to use and not available on a wide basis. Under the Grid concept disparate organizations generally defined as "virtual organizations" can share services i.e. sharing discipline specific computer applications, required to accomplish the specific scientific and engineering organizational goals and objectives. Grids are emerging as the new technology of the future. Grid technology has been enabled by the evolution of increasingly high speed networking. Without the evolution of high speed networking Grid technology would not have emerged. NASA/Marshall Space Flight Center's (MSFC) Flight Projects Directorate, Ground Systems Department is developing a Space-based Science Operations Grid prototype to provide to scientists and engineers the tools necessary to operate space-based science payloads/experiments and for scientists to conduct public and educational outreach. In addition Grid technology can provide new services not currently available to users. These services include mission voice and video, application sharing, telemetry management and display, payload and experiment commanding, data mining, high order data processing, discipline specific application sharing and data storage, all from a single grid portal. The Prototype will provide most of these services in a first step demonstration of integrated Grid and space-based science operations technologies. It will initially be based on the International Space Station science operational services located at the Payload Operations Integration Center at MSFC, but can be applied to many NASA projects including free flying satellites and future projects. The Prototype will use the Internet2 Abilene Research and Education Network that is currently a 10 Gb backbone network to reach the University of Alabama at Huntsville and several other, as yet unidentified, Space Station based science experimenters. There is an international aspect to the Grid involving the America's Pathway (AMPath) network, the Chilean REUNA Research and Education Network and the University of Chile in Santiago that will further demonstrate how extensive these services can be used. From the user's perspective, the Prototype will provide a single interface and logon to these varied services without the complexity of knowing the where's and how's of each service. There is a separate and deliberate emphasis on security. Security will be addressed by specifically outlining the different approaches and tools used. Grid technology, unlike the Internet, is being designed with security in mind. In addition we will show the locations, configurations and network paths associated with each service and virtual organization. We will discuss the separate virtual organizations that we define for the varied user communities. These will include certain, as yet undetermined, space-based science functions and/or processes and will include specific virtual organizations required for public and educational outreach and science and engineering collaboration. We will also discuss the Grid Prototype performance and the potential for further Grid applications both space-based and ground based projects and processes. In this paper and presentation we will detail each service and how they are integrated using Grid
HEALPix the Hierarchical Equal Area isoLatitude Pixelization is a versatile structure for the pixelization of data on the sphere. An associated library of computational algorithms and visualization software supports fast scientific applications executable directly on discretized spherical maps generated from very large volumes of astronomical data. Originally developed to address the data processing and analysis needs of the present generation of cosmic microwave background experiments (e.g., BOOMERANG, WMAP), HEALPix can be expanded to meet many of the profound challenges that will arise in confrontation with the observational output of future missions and experiments, including, e.g., Planck, Herschel, SAFIR, and the Beyond Einstein inflation probe. In this paper we consider the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere. We demonstrate how these are explicitly satisfied by HEALPix.
A computer program for use aboard a scientific-exploration spacecraft autonomously selects among goals specified in high-level requests and generates corresponding sequences of low-level commands, understandable by spacecraft systems. (As used here, 'goals' signifies specific scientific observations.) From a dynamic, onboard set of goals that could oversubscribe spacecraft resources, the program selects a non-oversubscribing subset that maximizes a quality metric. In an early version of the program, the requested goals are assumed to have fixed starting times and durations. Goals can conflict by exceeding a limit on either the number of separate goals or the number of overlapping goals making demands on the same resource. The quality metric used in this version is chosen to ensure that a goal will never be replaced by another having lower priority. At any time, goals can be added or removed, or their priorities can be changed, and the 'best' goal will be selected. Once a goal has been selected, the program implements a robust, flexible approach to generation of low-level commands: Rather than generate rigid sequences with fixed starting times, the program specifies flexible sequences that can be altered to accommodate run time variations.
An incremental approach to modernization of scientific software written in the Fortran 77 computing language has been developed. This approach makes it possible to preserve the investment in legacy Fortran software while augmenting the software with modern capabilities to satisfy expanded requirements. This approach could be advantageous (1) in situations in which major rewriting of application programs is undesirable or impossible, or (2) as a means of transition to major rewriting.
From its bold start nearly 30 years ago and continuing today, the NASA Advanced Supercomputing (NAS) facility at Ames Research Center has enabled remarkable breakthroughs in the space agency s science and engineering missions. Throughout this time, NAS experts have influenced the state-of-the-art in high-performance computing (HPC) and related technologies such as scientific visualization, system benchmarking, batch scheduling, and grid environments. We highlight the pioneering achievements and innovations originating from and made possible by NAS resources and know-how, from early supercomputing environment design and software development, to long-term simulation and analyses critical to design safe Space Shuttle operations and associated spinoff technologies, to the highly successful Kepler Mission s discovery of new planets now capturing the world s imagination.
An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources which subsequently enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in-situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data distributed through data centers such as the PO.DAAC, COAPS, NCAR, and many others to conduct their research. In typical investigations, scientists would engage in: search for data, evaluate the relevance of that data, download it, and then apply algorithms to identify trends. Such workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. NASA’s Surface Water and Ocean Topography (SWOT) mission is expected to produce massive amount of observational data during its 3-year nominal mission. Collections like SWOT challenges all existing Earth Science data archival, distribution and analysis paradigms. In this paper, we will discuss how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.
Introduction: Apollo Sample 73001/2 is a ~71cm long double drive tube consisting of an upper part (73002) and a lower part (73001) that contains regolith collected near Lara Crater at the Apollo 17 site, Station 3. The double drive tube is believed to have penetrated a lunar landslide deposit that was transported from the slope of the South Massif into the Taurus-Littrow Valley [1]. As part of the ANGSA (Apollo Next Generation Sample Analyses) initiative, preparing a preliminary examination (PE) catalog of 73001/2 is a crucial first step for the early identification of material types such as rock fragments and potential stratigraphy within the core. Many new curation and scientific tools such as X-ray computed tomography (XCT) [3], multi-spectral imaging [4], and gas extraction manifold with piercing tool [5-7], have been applied to the ANGSA core to benefit curation strategy, PE efforts, sample allocation to the planetary science community, and ultimately help to prepare for future sample return missions like Artemis. 73001/2 Preliminary Examination and Processing: Sample 73002 was successfully opened and extruded in Nov. 2019 and fully dissected at the end of 2021. Sample 73001 (Fig. 1) was successfully extruded in March 2022 after careful planning before opening the Core Sample Vacuum Container (CSVC) that was holding the drive tube of 73001. XCT, as part of PE, was used to scan the bottom and top part of the 73001 core tube within the CSVC prior to opening it to 1) facilitate non-destructive, rapid detection of any contamination potentials due to piercing of the CSVC during gas extraction [7]; and 2) to aid in the Artemis sample tool development and provide data on the knife edge seal of the CSVC. This knowledge will help us connect the mechanics of the implemented design (i.e., XCT data) to the performance of the seal (i.e., data on the gas samples will tell us how well the seal preserved the volatile record of lunar samples). Both type of information will feed forward into Artemis tool and storage strategies for future samples. Results and Lessons learned: The XCT data of the CSVC and core tube within showed that the bottom Teflon cap was not pierced during gas extraction (Fig. 1c) and thus, the sample integrity remained guaranteed during piercing and subsequent gas extraction. However, the XCT scan of the top of the core (Fig. 1b) revealed that the drive tube was overfilled with lunar soil and the tool that keeps the soil constrained within the drive tube was not fully deployed. These preliminary data allowed us to implement the necessary steps to prevent loss of sample integrity, including any potential stratigraphy shifts during extrusion. Processing Apollo core 73001/2, creating an informative PE catalog, and applying new and refined tools and technologies for sample analyses are invaluable activities that will assist in circumventing any potential pitfalls, aid in the characterization of samples, and help in the assessment of how well any lunar material has been collected and preserved in the past. This will aid in designing future sample collections and curation procedures and help to prepare for future human exploration and sampling missions such as Artemis. References: [1] Schmitt H. (2017) Icarus 298, 2-33. [3] Zeigler et al. (2021) LPSC 52nd, #2632; [4] Sun et al. (2021), LPSC 52nd, #1789; [5] Parai et al. (2021), LPSC 52nd #2665; [6] Schild et al. (2021) LPSC 52nd #1888; [7] McDonald (2022) ESL 2022.
Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.
In a previous report the design concepts of Charon were presented. Charon is a toolkit that aids engineers in developing scientific programs for structured-grid applications to be run on MIMD parallel computers. It constitutes an augmentation of the general-purpose MPI-based message-passing layer, and provides the user with a hierarchy of tools for rapid prototyping and validation of parallel programs, and subsequent piecemeal performance tuning. Here we describe the implementation of the domain decomposition tools used for creating data distributions across sets of processors. We also present the hierarchy of parallelization tools that allows smooth translation of legacy code (or a serial design) into a parallel program. Along with the actual tool descriptions, we will present the considerations that led to the particular design choices. Many of these are motivated by the requirement that Charon must be useful within the traditional computational environments of Fortran 77 and C. Only the Fortran 77 syntax will be presented in this report.