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At least 1,243 records · Page 69

MOS 2.0: The Next Generation in Mission Operations Systems

A Mission Operations System (MOS) or Ground System constitutes that portion of an overall space mission Enterprise that resides here on Earth. Over the past two decades, technological innovations in computing and software technologies have allowed an MOS to support ever more complex missions while consuming a decreasing fraction of Project development budgets. Despite (or perhaps, because of) such successes, it is routine to hear concerns about the cost of MOS development. At the same time, demand continues for Ground Systems which will plan more spacecraft activities with fewer commanding errors, provide scientists and engineers with more autonomous functionality, process and manage larger and more complex data more quickly, all while requiring fewer people to develop, deploy, operate and maintain them. One successful approach to such concerns over this period is a multimission approach, based on the reuse of portions (most often software) developed and used in previous missions. The Advanced Multi-Mission Operations System (AMMOS), developed for deep-space science missions, is one successful example of such an approach. Like many computing-intensive systems, it has grown up in a near-organic fashion from a relatively simple set of tools into a complexly interrelated set of capabilities. Such systems, like a city lacking any concept of urban planning, can and will grow in ways that are neither efficient nor particularly easy to sustain. To meet the growing demands and unyielding constraints placed on ground systems, a new approach is necessary. Under the aegis of a multi-year effort to revitalize the AMMOS's multimission operations capabilities, we are utilizing modern practices in systems architecting and model-based engineering to create the next step in Ground Systems: MOS 2.0. In this paper we outline our work (ongoing and planned) to architect and design a multimission MOS 2.0, describe our goals and measureable objectives, and discuss some of the benefits that this top-down, architectural approach holds for creating a more flexible and capable MOS for Missions while holding the line on cost.

ground systems↗

Cloud-Based Time Series Analysis of Extremes: Use Cases and Applications

"Extreme weather events, such as hurricanes, tornadoes, floods, droughts, heatwaves, and blizzards, can cause widespread damage, disrupting ecosystems, agricultural production, and economies. The frequency and intensity of these events have been increasing, likely due to climate change, raising concerns and the need for more accurate analysis and predictions. NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) has migrated its long-term historical datasets, including precipitation data from MERRA-2 reanalysis, GLDAS land data assimilation, and IMERG satellite observations, to the cloud. This cloud-stored data enables scientists and researchers to utilize cloud computing for advanced modeling and forecasting of extreme weather events, eliminating the need to download large datasets. In this presentation, we will provide an overview of the cloud-based data and services managed by GES DISC; demonstrate methods for accessing and analyzing time series data stored in the cloud; and compare results across various datasets to address critical questions related to extreme precipitation. We will present use cases including: 1. Determining the average total precipitation in California during January and February from 2000 to 2024, and identifying anomalous precipitation in 2021. 2. Calculating the 10, 20, 50, and 100-year return periods for maximum daily rainfall based on 25 years of historical precipitation data (2000-2024) for Maryland.

time series↗

VisIO: enabling interactive visualization of ultra-scale, time-series data via high-bandwidth distributed I/O systems

Petascale simulations compute at resolutions ranging into billions of cells and write terabytes of data for visualization and analysis. Interactive visuaUzation of this time series is a desired step before starting a new run. The I/O subsystem and associated network often are a significant impediment to interactive visualization of time-varying data; as they are not configured or provisioned to provide necessary I/O read rates. In this paper, we propose a new I/O library for visualization applications: VisIO. Visualization applications commonly use N-to-N reads within their parallel enabled readers which provides an incentive for a shared-nothing approach to I/O, similar to other data-intensive approaches such as Hadoop. However, unlike other data-intensive applications, visualization requires: (1) interactive performance for large data volumes, (2) compatibility with MPI and POSIX file system semantics for compatibility with existing infrastructure, and (3) use of existing file formats and their stipulated data partitioning rules. VisIO, provides a mechanism for using a non-POSIX distributed file system to provide linear scaling of 110 bandwidth. In addition, we introduce a novel scheduling algorithm that helps to co-locate visualization processes on nodes with the requested data. Testing using VisIO integrated into Para View was conducted using the Hadoop Distributed File System (HDFS) on TACC's Longhorn cluster. A representative dataset, VPIC, across 128 nodes showed a 64.4% read performance improvement compared to the provided Lustre installation. Also tested, was a dataset representing a global ocean salinity simulation that showed a 51.4% improvement in read performance over Lustre when using our VisIO system. VisIO, provides powerful high-performance I/O services to visualization applications, allowing for interactive performance with ultra-scale, time-series data.

97 MATHEMATICS AND COMPUTING↗

Generalized and Mechanistic PV Module Performance Prediction From Computer Vision and Machine Learning on Electroluminescence Images

Electroluminescence (EL) imaging of photovoltiac (PV) modules offers high-speed, high-resolution information about device performance, affording opportunities for greater insight and efficiency in module characterization across manufacturing, research and development, and power plant operations and management. Predicting module electrical properties from EL image features is a critical step toward these applications. In this article, we demonstrate quantification of both generalized and performance mechanism-specific EL image features, using pixel intensity-based and machine learning classification algorithms. From EL image features, we build predictive models for PV module power and series resistance, using time-series current-voltage (I-V) and EL data obtained stepwise on five brands of modules spanning three Si cell types through two accelerated exposures: damp heat (DH) (85°C/85% RH) and thermal cycling (TC) (IEC 61215). Overall, 195 pairs of EL images and I-V characteristics were analyzed, yielding 11700 individual PV cell images. A convolutional neural network was built to classify cells by the severity of busbar corrosion with high accuracy (95%). Generalized power predictive models estimated the maximum power of PV modules from EL images with high confidence and an adjusted-R 2 of 0.88, across all module brands and cell types in extended DH and TC exposures. Mechanistic degradation prediction was demonstrated by quantification of busbar corrosion in EL images of three module brands in DH, and subsequent modeling of series resistance using these mechanism-specific EL image features. For modules exhibiting busbar corrosion, we demonstrated series resistance predictive models with adjusted-R 2 of up to 0.73.

14 SOLAR ENERGY↗

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗

The effect of gravity waves on the global mean temperature and composition structure of the upper atmosphere

Formulas are presented that parameterize the heating rate and coefficient of turbulent heat conduction produced by saturated internal gravity waves (IGW) in the upper atmosphere. Estimates of these values are made using observational data. The parameterization of IGW influences are introduced into a one-dimensional model of global mean thermal and composition balances of the upper atmosphere. Computations are performed for different values of IGW energy fluxes entering into the upper atmosphere from below. It is shown that realistic vertical profiles of the global mean temperature can be obtained using different values of IGW energy flux into the upper atmosphere. Increasing the IGW intensity leads not only to an increase of the heating rate due to wave enery dissipation, but also to an increase of the heating rate due to wave energy dissipation, but also to an increase in the coefficient of turbulent heat conduction and cooling rate produced by turbulence generated by the wave. So, near an altitude of 100 km the main part of solar heating is compensated by infrared cooling on one hand, and the main part of wave dissipation heating is compensated by turbulent cooling on the other hand. These quasi-balances generally hold for different values of IGW intensity.

Gavrilov, Nikolai M.↗

Calibration of Direct Velocimetry Using Hot Wire Anemometry

We studied the functionality of the IFA300 Hot Wire Anemometry system and its feasibility for the calibration of Direct Estimator Velocimetry (DEV) using Laser Induced Florescence (LIF). The experimental setup consisted of a single-wire hot wire probe measuring one component of velocity, the anemometry computational hardware and software, an HP oscilloscope, and a table fan to produce a simple flow with fluctuations. Measurements were taken at several points in the stream wise and transverse directions in the flow and various parameters recorded such as mean velocities temperature, turbulence intensities, skewness coefficients and flatness coefficients. The IFA300 software also allowed us to perform statistical manipulations such as spectrum analysis on velocities samples and correlation. Utilization of data files, also produced by the anemometry software, and post analysis were performed to produce graphical representations of turbulent intensity versus probe position and a flow field velocity profile. We concluded that the IFA300 Hot Wire Anemometry system is a reliable and functional method for calibration of DEV using LIF. Our future intentions are to set up a test chamber such that both velocity measurement techniques can be applied simultaneously, thus the calibration.

Holland, Michael L.↗

ON COMPUTING UPPER LIMITS TO SOURCE INTENSITIES

A common problem in astrophysics is determining how bright a source could be and still not be detected in an observation. Despite the simplicity with which the problem can be stated, the solution involves complicated statistical issues that require careful analysis. In contrast to the more familiar confidence bound, this concept has never been formally analyzed, leading to a great variety of often ad hoc solutions. Here we formulate and describe the problem in a self-consistent manner. Detection significance is usually defined by the acceptable proportion of false positives (background fluctuations that are claimed as detections, or Type I error), and we invoke the complementary concept of false negatives (real sources that go undetected, or Type II error), based on the statistical power of a test, to compute an upper limit to the detectable source intensity. To determine the minimum intensity that a source must have for it to be detected, we first define a detection threshold and then compute the probabilities of detecting sources of various intensities at the given threshold. The intensity that corresponds to the specified Type II error probability defines that minimum intensity and is identified as the upper limit. Thus, an upper limit is a characteristic of the detection procedure rather than the strength of any particular source. It should not be confused with confidence intervals or other estimates of source intensity. This is particularly important given the large number of catalogs that are being generated from increasingly sensitive surveys. We discuss, with examples, the differences between these upper limits and confidence bounds. Both measures are useful quantities that should be reported in order to extract the most science from catalogs, though they answer different statistical questions: an upper bound describes an inference range on the source intensity, while an upper limit calibrates the detection process. We provide a recipe for computing upper limits that applies to all detection algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On the arithmetic intensity of high-order finite-volume discretizations for hyperbolic systems of conservation laws

It has been conjectured that higher-order discretizations for partial differential equations will have advantages over the lower-order counterparts commonly used today. The reasoning is that the increase in arithmetic operations will be more than offset by the reduction in data transfers and the increase in concurrent floating-point units. To evaluate this conjecture, the arithmetic intensity of a class of high-order finite-volume discretizations for hyperbolic systems of conservation laws is theoretically analyzed for spatial discretizations from orders three through eight in arbitrary dimensions. Additionally, three cache models are considered: the limiting cases of no cache and infinite cache as well as a finite-sized cache model. Models are validated experimentally by measuring floating-point operations and data transfers on an IBM Blue Gene/Q node. Theory and experiments demonstrate that high-order finite-volume methods will be able to provide increases in arithmetic intensity that will be necessary to make better utilization of on-node floating-point capability.

97 MATHEMATICS AND COMPUTING↗

Veggie Hardware Validation Test Preliminary Results and Lessons Learned

The Veggie hardware validation test, VEG-01, was conducted on the International Space Station during Expeditions 39 and 40 from May through June of 2014. The Veggie hardware and the VEG-01 experiment payload were launched to station aboard the SpaceX-3 resupply mission in April, 2014. Veggie was installed in an Expedite-the-Processing-of-Experiments-to-Space-Station (ExPRESS) rack in the Columbus module, and the VEG-01 validation test was initiated. Veggie installation was successful, and power was supplied to the unit. The hardware was programmed and the root mat reservoir and plant pillows were installed without issue. As expected, a small amount of growth media was observed in the sealed bags which enclosed the plant pillows when they were destowed. Astronaut Steve Swanson used the wet/dry vacuum to clean up the escaped particles. Water insertion or priming the first plant pillow was unsuccessful as an issue prevented water movement through the quick disconnect. All subsequent pillows were successfully primed, and the initial pillow was replaced with a backup pillow and successfully primed. Six pillows were primed, but only five pillows had plants which germinated. After about a week and a half it was observed that plants were not growing well and that pillow wicks were dry. This indicated that the reservoir was not supplying sufficient water to the pillows via wicking, and so the team reverted to an operational fix which added water directly to the plant pillows. Direct watering of the pillows led to a recovery in several of the stressed plants; a couple of which did not recover. An important lesson learned involved Veggie's bellows. The bellows tended to float and interfere with operations when opened, so Steve secured them to the baseplate during plant tending operations. Due to the perceived intensity of the LED lights, the crew found it challenging to both work under the lights and read crew procedures on their computer. Although the lights are not a safety hazard, for visual comfort crewmembers were advised to wear sunglasses when working with the plants and then they can lift glasses to read procedures. Steve Swanson had already trail-blazed this procedure when he initiated VEG-01. The temperature and humidity data logger was relocated mid-experiment to provide measurements on both sides of the unit. Images of the plants were downlinked weekly, and videos of installation and harvest were recorded. This imaging frequency was not sufficient to monitor and respond to changes in plant growth. Plants, samples, and data loggers will be returned on SpaceX-4, scheduled to return the fall of 2014. Lessons learned will be translated into hardware and operational modifications for future Veggie payloads.

International Space Station↗

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part I

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity as well as the mean temperature and root mean square (rms) temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to M0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report and are available from the NASA STI office. The final portion of the data will be published in a future report, Part II, along with CFD predictions of the complex cooling film flow.

IR camera Measurments↗

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part 1

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity as well as the mean temperature and root mean square (rms) temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to M0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report and are available from the NASA STI office. The final portion of the data will be published in a future report, Part II, along with CFD predictions of the complex cooling film flow.

Raman Scattering↗

Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore how different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Impact of New Technologies on Radiation Oncology Events and Trends in the Past Decade: An Institutional Experience

Purpose: To review the type and frequency of patient events from external-beam radiotherapy over a time period sufficiently long to encompass significant technology changes. Methods and Materials: Ten years of quality assurance records from January 2001 through December 2010 were retrospectively reviewed to determine the frequency of events affecting patient treatment from four radiation oncology process steps: simulation, treatment planning, data entry/transfer, and treatment delivery. Patient events were obtained from manual records and, from May 2007 onward, from an institution-wide database and reporting system. Events were classified according to process step of origination and segregated according to the most frequently observed event types. Events from the institution-wide database were evaluated to determine time trends. Results: The overall event rate was 0.93% per course of treatment, with a downward trend over time led by a decrease in treatment delivery events. The frequency of certain event types, particularly in planning and treatment delivery, changed significantly over the course of the study, reflecting technologic and process changes. Treatments involving some form of manual intervention carried an event risk four times higher than those relying heavily on computer-aided design and delivery. Conclusions: Although the overall event rate was low, areas for improvement were identified, including manual calculations and data entry, late-day treatments, and staff overreliance on computer systems. Reducing the incidence of pretreatment events is of particular importance because these were more likely to occur several times before detection and were associated with larger dosimetric impact. Further improvements in quality assurance systems and reporting are imperative, given the advent of electronic charting, increasing reliance on computer systems, and the potentially severe consequences that can arise from mistakes involving complex intensity-modulated or image-guided treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

MultispeQ Beta: a tool for large-scale plant phenotyping connected to the open PhotosynQ network

Large-scale high-throughput plant phenotyping (sometimes called phenomics) is becoming increasingly important in plant biology and agriculture and is essential to cutting-edge plant breeding and management approaches needed to meet the food and fuel needs for the next century. Currently, the application of these approaches is severely limited by the availability of appropriate instrumentation and by the ability to communicate experimental protocols, results and analyses. To address these issues, we have developed a low-cost, yet sophisticated open-source scientific instrument designed to enable communities of researchers, plant breeders, educators, farmers and citizen scientists to collect high-quality field data on a large scale. The MultispeQ provides measurements in the field or laboratory of both, environmental conditions (light intensity and quality, temperature, humidity, CO 2 levels, time and location) and useful plant phenotypes, including photosynthetic parameters—photosystem II quantum yield (Φ II ), non-photochemical exciton quenching (NPQ), photosystem II photoinhibition, light-driven proton translocation and thylakoid proton motive force, regulation of the chloroplast ATP synthase and potentially many others—and leaf chlorophyll and other pigments. Plant phenotype data are transmitted from the MultispeQ to mobile devices, laptops or desktop computers together with key metadata that gets saved to the PhotosynQ platform (https://photosynq.org) and provides a suite of web-based tools for sharing, visualization, filtering, dissemination and analyses. We present validation experiments, comparing MultispeQ results with established platforms, and show that it can be usefully deployed in both laboratory and field settings. We present evidence that MultispeQ can be used by communities of researchers to rapidly measure, store and analyse multiple environmental and plant properties, allowing for deeper understanding of the complex interactions between plants and their environment.

47 OTHER INSTRUMENTATION↗

Strangers in a foreign land: ‘Yeastizing’ plant enzymes

Abstract Expressing plant metabolic pathways in microbial platforms is an efficient, cost‐effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour‐intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost‐effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data‐driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design‐build‐test cycle.

59 BASIC BIOLOGICAL SCIENCES↗

MaDaTS: Managing Data on Tiered Storage for Scientific Workflows

Scientific workflows are increasingly used in High Performance Computing (HPC) environments to manage complex simulation and analyses, often consuming and generating large amounts of data. However, workflow tools have limited support for managing the input, output and intermediate data. The data elements of a workflow are often managed by the user through scripts or other ad-hoc mechanisms. Technology advances for future HPC systems is redefining the memory and storage subsystem by introducing additional tiers to improve the I/O performance of data-intensive applications. These architectural changes introduce additional complexities to managing data for scientific workflows. Thus, we need to manage the scientific workflow data across the tiered storage system on HPC machines. In this paper, we present the design and implementation of MaDaTS (Managing Data on Tiered Storage for Scientific Workflows), a software architecture that manages data for scientific workflows. We introduce Virtual Data Space (VDS), an abstraction of the data in a workflow that hides the complexities of the underlying storage system while allowing users to control data management strategies. We evaluate the data management strategies with real scientific and synthetic workflows, and demonstrate the capabilities of MaDaTS. Our experiments demonstrate the flexibility, performance and scalability gains of MaDaTS as compared to the traditional approach of managing data in scientific workflows.

Ghoshal, Devarshi↗

Draco,Version 6.x.x

Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.

Thompson, Kelly↗