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Assessing data change in scientific datasets

Summary Scientific datasets are growing rapidly and becoming critical to next‐generation scientific discoveries. The validity of scientific results relies on the quality of data used and data are often subject to change, for example, due to observation additions, quality assessments, or processing software updates. The effects of data change are not well understood and difficult to predict. Datasets are often repeatedly updated and recomputing derived data products quickly becomes time consuming and resource intensive and may in some cases not even be necessary, thus delaying scientific advance. Despite its importance, there is a lack of systematic approaches for best comparing data versions to quantify the changes, and ad‐hoc or manual processes are commonly used. In this article, we propose a novel hierarchical approach for analyzing data changes, including real‐time (online) and offline analyses. We employ a variety of fast‐to‐compute numerical analyses, graphical data change representations, and more resource‐intensive recomputations of a subset of the data product. We illustrate the application of our approach using three scientific diverse use cases, namely, satellite, cosmological, and x‐ray data. The results show that a variety of data change metrics should be employed to enable a comprehensive representation and qualitative evaluation of data changes.

97 MATHEMATICS AND COMPUTING↗

Code Verification and Solution Verification framework in pin-resolved neutron transport code MPACT

Program verification in scientific computing encompasses the application of formal and mathematical techniques to a scientific computing code for its credibility, accuracy, and validity. Code Verification identifies bugs and performance issues in the software development stage. Solution Verification assesses the applicability of the code and the accuracy of the solution to problems of interest. Both activities utilize application cases and quantify the error against prescribed acceptance criteria. However, simply executing more application cases does not guarantee stronger or more comprehensive credibility. Here, we establish a verification framework that involves Code Verification and Solution Verification, both of which work together such that the overarching goal of “converge to the correct answer for the intended application” can be reasonably inferred. The application of such a verification framework is demonstrated using the pin-resolved neutron transport code MPACT, where standard unit tests and regression tests are covered, and where the Method of Exact Solutions and the Method of Manufactured Solutions are successfully used. Additionally, the applicability of Method of Manufactured Solutions is extended to the OECD/NEA C5G7 benchmark problems of practical material and geometric configurations. Solution Verification activities are demonstrated on a practical hierarchy of application models of increasing complexity ranging from 2D pin cell problems to 3D assembly problems. The convergence behavior and rate of convergence with respect to each individual variable are studied and provided. This framework can be adapted broadly to other fields involving scientific computing codes.

97 MATHEMATICS AND COMPUTING↗

PI in the sky: The astronaut science advisor on SLS-2

The Astronaut Science Advisor (ASA, also known as Principal-Investigator-in-a-Box) is an advanced engineering effort to apply expert systems technology to experiment monitoring and control. Its goal is to increase the scientific value of information returned from experiments on manned space missions. The first in-space test of the system will be in conjunction with Professor Larry Young's (MIT) vestibulo-ocular 'Rotating Dome' experiment on the Spacelab Life Sciences 2 mission (STS-58) in the Fall of 1993. In a cost-saving effort, off-the-shelf equipment was employed wherever possible. Several modifications were necessary in order to make the system flight-worthy. The software consists of three interlocking modules. A real-time data acquisition system digitizes and stores all experiment data and then characterizes the signals in symbolic form; a rule-based expert system uses the symbolic signal characteristics to make decisions concerning the experiment; and a highly graphic user interface requiring a minimum of user intervention presents information to the astronaut operator. Much has been learned about the design of software and user interfaces for interactive computing in space. In addition, we gained a great deal of knowledge about building relatively inexpensive hardware and software for use in space. New technologies are being assessed to make the system a much more powerful ally in future scientific research in space and on the ground.

Hazelton, Lyman R.↗

Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels

58 GEOSCIENCES↗

On the Fundamental and Practical Aspects of Modeling Complex Electrochemical Kinetics and Transport

Numerous technologies, such as batteries and fuel cells, depend on electrochemical kinetics. In some cases, the responsible electrochemistry and charged-species transport is complex. However, to date, there are essentially no general-purpose modeling capabilities that facilitate the incorporation of thermodynamic, kinetic, and transport complexities into the simulation of electrochemical processes. A vast majority of the modeling literature uses only a few (often only one) global charge-transfer reactions, with the rates expressed using Butler-Volmer approximations. The objective of the present paper is to identify common aspects of electrochemistry, seeking a foundational basis for designing and implementing software with general applicability across a wide range of materials sets and applications. The development of new technologies should be accelerated and improved by enabling the incorporation of electrochemical complexity (e.g., multi-step, elementary charge-transfer reactions and as well as supporting ionic and electronic transport) into the analysis and interpretation of scientific results. The spirit of the approach is analogous to the role that Chemkin has played in homogeneous chemistry modeling, especially combustion. The Cantera software, which already has some electrochemistry capabilities, forms the foundation for future capabilities expansion.

30 DIRECT ENERGY CONVERSION↗

Improving the Automatic Inversion of Digital Alouette/ISIS Ionogram Reflection Traces into Topside Electron Density Profiles

The topside sounders of the International Satellites for Ionospheric Studies (ISIS) program were designed as analog systems. The resulting ionograms were displayed on 35 mm film for analysis by visual inspection. Each of these satellites, launched between 1962 and 1971, produced data for 10 to 20 years. A number of the original telemetry tapes from this large data set have been converted directly into digital records. Software, known as the Topside Ionogram Scalar With True-Height (TOPIST) algorithm, has been produced and used for the automatic inversion of the ionogram reflection traces on more than 100,000 ISIS-2 digital topside ionograms into topside vertical electron density profiles Ne(h). Here we present some topside ionospheric solar cycle variations deduced from the TOPIST database to illustrate the scientific benefit of improving and expanding the topside ionospheric Ne(h) database. The profile improvements will be based on improvements in the TOPIST software motivated by direct comparisons between TOPIST profiles and profiles produced by manual scaling in the early days of the ISIS program. The database expansion will be based on new software designed to overcome limitations in the original digital topside ionogram database caused by difficulties encountered during the analog-to-digital conversion process in the detection of the ionogram frame sync pulse and/or the frequency markers. This improved and expanded TOPIST topside Ne(h) database will greatly enhance investigations into both short- and long-term ionospheric changes, e.g., the observed topside ionospheric responses to magnetic storms, induced by interplanetary magnetic clouds, and solar cycle variations, respectively.

Benson, Robert F.↗

Scientific Visualization & Modeling for Earth Systems Science Education

Providing research experiences for undergraduate students in Earth Systems Science (ESS) poses several challenges at smaller academic institutions that might lack dedicated resources for this area of study. This paper describes the development of an innovative model that involves students with majors in diverse scientific disciplines in authentic ESS research. In studying global climate change, experts typically use scientific visualization techniques applied to remote sensing data collected by satellites. In particular, many problems related to environmental phenomena can be quantitatively addressed by investigations based on datasets related to the scientific endeavours such as the Earth Radiation Budget Experiment (ERBE). Working with data products stored at NASA's Distributed Active Archive Centers, visualization software specifically designed for students and an advanced, immersive Virtual Reality (VR) environment, students engage in guided research projects during a structured 6-week summer program. Over the 5-year span, this program has afforded the opportunity for students majoring in biology, chemistry, mathematics, computer science, physics, engineering and science education to work collaboratively in teams on research projects that emphasize the use of scientific visualization in studying the environment. Recently, a hands-on component has been added through science student partnerships with school-teachers in data collection and reporting for the GLOBE Program (GLobal Observations to Benefit the Environment).

Chaudhury, S. Raj↗

The New Cloud Absorption Radiometer (CAR) Software: One Model for NASA Remote Sensing Virtual Instruments

The Cloud Absorption Radiometer (CAR) instrument has been the most frequently used airborne instrument built in-house at NASA Goddard Space Flight Center, having flown scientific research missions on-board various aircraft to many locations in the United States, Azores, Brazil, and Kuwait since 1983. The CAR instrument is capable of measuring scattered light by clouds in fourteen spectral bands in UV, visible and near-infrared region. This document describes the control, data acquisition, display, and file storage software for the new version of CAR. This software completely replaces the prior CAR Data System and Control Panel with a compact and robust virtual instrument computer interface. Additionally, the instrument is now usable for the first time for taking data in an off-aircraft mode. The new instrument is controlled via a LabVIEW v5. 1.1-developed software interface that utilizes, (1) serial port writes to write commands to the controller module of the instrument, and (2) serial port reads to acquire data from the controller module of the instrument. Step-by-step operational procedures are provided in this document. A suite of other software programs has been developed to complement the actual CAR virtual instrument. These programs include: (1) a simulator mode that allows pretesting of new features that might be added in the future, as well as demonstrations to CAR customers, and development at times when the instrument/hardware is off-location, and (2) a post-experiment data viewer that can be used to view all segments of individual data cycles and to locate positions where 'start' and stop' byte sequences were incorrectly formulated by the instrument controller. The CAR software described here is expected to be the basis for CAR operation for many missions and many years to come.

Roth, Don J.↗

Throughput Analytics of Data Transfer Infrastructures

To support increasingly distributed scientific and big-data applications, powerful data transfer infrastructures are being built with dedicated networks and software frameworks customized to distributed file systems and data transfer nodes. The data transfer performance of such infrastructures critically depends on the combined choices of file, disk, and host systems as well as network protocols and file transfer software, all of which may vary across sites. The randomness of throughput measurements makes it challenging to assess the impact of these choices on the performance of infrastructure or its parts. We propose regression-based throughput profiles by aggregating measurements from sites of the infrastructure, with RTT as the independent variable. The peak values and convex-concave shape of a profile together determine the overall throughput performance of memory and file transfers, and its variations show the performance differences among the sites. We then present projection and difference operators, and coefficients of throughput profiles to characterize the performance of infrastructure and its parts, including sites and file transfer tools. In particular, the utilization-concavity coefficient provides a value in the range [0, 1] that reflects overall transfer effectiveness. We present results of measurements collected using (i) testbed experiments over dedicated 0–366 ms 10 Gbps connections with combinations of TCP versions, file systems, host systems and transfer tools, and (ii) Globus GridFTP transfers over production infrastructure with varying site configurations.

Rao, Nageswara S.↗

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗

Drilling Down I/O Bottlenecks with Cross-layer I/O Profile Exploration

I/O performance monitoring tools such as Darshan and Recorder collect I/O-related metrics on production systems and help understand the applications' behavior. However, some gaps prevent end-users from seeing the whole picture when it comes to detecting and drilling down to the root causes of I/O performance slowdowns and where those problems originate. These gaps arise from limitations in the available metrics, their collection strategy, and the lack of translation to actionable items that could advise on optimizations. This paper highlights such gaps and proposes solutions to drill down to the source code level to pinpoint the root causes of I/O bottlenecks scientific applications face by relying on cross-layer analysis combining multiple performance metrics related to I/O software layers. We demonstrate with two real applications how metrics collected in high-level libraries (which are closer to the data models used by an application), enhanced by source-code insights and natural language translations, can help streamline the understanding of I/O behavior and provide guidance to end-users, developers, and supercomputing facilities on how to improve I/O performance. Using this cross-layer analysis and the heuristic recommendations, we attained up to 6.9× speedup from run-as-is executions.

Ather, Hammad↗

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Status and projections of the NAS program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Background leading to the NAS program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration are presented. Program status, near-term plans, and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, Frank R.↗

Status and projections of the NAS Program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the new Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Presented here is the background leading to the NAS Program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration. Program status, near-term plans and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, F. R.↗

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

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.

Larson, Jay W.↗

BATSE Solar Flare Spectroscopy

This final report describes the progress originally proposed: (1) the continued improvement of a software and database environment capable of supporting all users of BATSE solar data as well as providing scientific expertise and effort to the BATSE solar community; (2) the continued participation with the PI team and other guest investigators in the detailed analysis of the BATSE detectors' response at low energies; (3) using spectroscopic techniques to fully exploit the potential of electron time-of-flight studies; and, (4) a full search for flare gamma-ray line emission at 2.2 MeV from all GOES X-class flares observed with BATSE.

Schwartz, R. A.↗

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗

Facilitating Science--The International Space Station Fluids and Combustion Facility

Scientists in many fields would like to perform experiments on the International Space Station (ISS) to take advantage of the unique environment of microgravity (which is the near-absence of gravity). The ISS will provide the opportunity for scientists to perform microgravity tests over much longer time periods than previously available on the space shuttle--months rather than hours or days--providing more data that could lead to new discoveries. Many of the experiments on ISS will be conducted through the use of new microgravity science facilities. A microgravity science facility is a complete system of on-orbit and ground (on-Earth) hardware, software, operations, and plans that have been optimized to perform sustained microgravity research in one or two scientific disciplines. The facility concept includes hardware that remains on-orbit (because of its general usefulness) and a small amount of unique hardware that is developed for each principal investigator. Such unique hardware customizes the facility to perform a given principal investigator's experiment effectively. Many facilities are planned for the ISS to accommodate scientists' needs. While the quality and quantity of scientific data are being improved, per-experiment costs will be lowered relative to other ways of performing such experiments. The NASA Lewis Research Center is developing a Fluids and Combustion Facility (FCF) to perform microgravity fluids and combustion experiments on the ISS. The FCF will be the lowest cost, most resource efficient approach to performing fluid physics and combustion science experiments on the ISS. Experiments performed in the FCF will be 3 to 9 times less expensive than similar Spacelab experiments. Moreover, use of key ISS resources, such as upmass, power, cooling, and astronaut crew time, will be cut by the same factor.

Winsa, Edward A.↗