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At least 1,639 records · Page 91

Validation of Synthetic U.S. Electric Power Distribution System Data Sets

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. Furthermore, it also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Assessment of Soil Moisture Data Requirements by the Potential SMAP Data User Community: Review of SMAP Mission User Community

NASA's Soil Moisture Active and Passive (SMAP) mission is planned for launch in October 2014 and will provide global measurements of soil moisture and freeze thaw state. The project is driven by both basic research and applied science goals. Understanding how application driven end-users will apply SMAP data, prior to the satellite's launch, is an important goal of NASA's applied science program and SMAP mission success. Because SMAP data are unique, there are no direct proxy data sets that can be used in research and operational studies to determine how the data will interact with existing processes. The objective of this study is to solicit data requirements, accuracy needs, and current understanding of the SMAP mission from the potential user community. This study showed that the data to be provided by the SMAP mission did substantially meet the user community needs. Although there was a broad distribution of requirements stated, the SMAP mission fit within these requirements.

applications↗

Predicting cancer rates in astronauts from animal carcinogenesis studies and cellular markers

The radiation space environment includes particles such as protons and multiple species of heavy ions, with much of the exposure to these radiations occurring at extremely low average dose-rates. Limitations in databases needed to predict cancer hazards in human beings from such radiations are significant and currently do not provide confidence that such predictions are acceptably precise or accurate. In this article, we outline the need for animal carcinogenesis data based on a more sophisticated understanding of the dose-response relationship for induction of cancer and correlative cellular endpoints by representative space radiations. We stress the need for a model that can interrelate human and animal carcinogenesis data with cellular mechanisms. Using a broad model for dose-response patterns which we term the "subalpha-alpha-omega (SAO) model", we explore examples in the literature for radiation-induced cancer and for radiation-induced cellular events to illustrate the need for data that define the dose-response patterns more precisely over specific dose ranges, with special attention to low dose, low dose-rate exposure. We present data for multiple endpoints in cells, which vary in their radiosensitivity, that also support the proposed model. We have measured induction of complex chromosome aberrations in multiple cell types by two space radiations, Fe-ions and protons, and compared these to photons delivered at high dose-rate or low dose-rate. Our data demonstrate that at least three factors modulate the relative efficacy of Fe-ions compared to photons: (i) intrinsic radiosensitivity of irradiated cells; (ii) dose-rate; and (iii) another unspecified effect perhaps related to reparability of DNA lesions. These factors can produce respectively up to at least 7-, 6- and 3-fold variability. These data demonstrate the need to understand better the role of intrinsic radiosensitivity and dose-rate effects in mammalian cell response to ionizing radiation. Such understanding is critical in extrapolating databases between cellular response, animal carcinogenesis and human carcinogenesis, and we suggest that the SAO model is a useful tool for such extrapolation.

Non-NASA Center↗

Usage of Data-Encoded Web Maps with Client Side Color Rendering for Combined Data Access, Visualization and Modeling Purposes

Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.

Pliutau, Denis↗

Characterizing manufacturing wastewater in the United States for the purpose of analyzing energy requirements for reuse

This paper seeks to inform an improved understanding of the energy tradeoff associated with on-site manufacturing water reuse in the United States from a lifecycle perspective, in part by developing an analytical framework for understanding when this tradeoff for reuse is beneficial. We survey the literature to assess the current state of reuse and its motives and barriers in the United States, before synthesizing information from publicly available EPA data on contaminants in US manufacturing wastewaters and technologies for treating them. Using the available data, we derive a set of “ubiquitous contaminants” among the top ten in terms of mass discharged in more than half of US manufacturing subsectors (NAICS 31–33) according to EPA permit data. We also present information on proven treatment trains and their energy requirements. We then compare water quality requirements for specific contaminants in reclaimed water to those characteristic of wastewater streams currently being discharged from manufacturing plants into surface waters to highlight sectors with reuse opportunities that could require little cost to realize, such as primary metals and, to a lesser extent, petroleum and coal products. We conclude by highlighting data limitations that need to be rectified before applying the framework more broadly and discussing how these data gaps could be filled. Better understanding the relationship between energy and water in the context of on-site manufacturing water reuse would allow manufacturers to improve resiliency by reducing regulatory, physical, and reputational risks while lessening their footprint on local watersheds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Analysis of terrestrial conditions and dynamics

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

Goward, S. N.↗

User friendly database for Neptune planetary radio astronomy observations

Planetary Radio Astronomy (PRA) data from the Voyager Neptune encounter were cleaned and reformatted in a variety of formats. Most of these formats are new and have been specifically designed to provide easy access and use of the data without the need to understand esoteric characteristics of the PRA instrument or the Voyager spacecraft. Several data sets were submitted to the Planetary Data System (PDS) and have either appeared already on peer reviewed CDROM's or are in the process of being reviewed for inclusion in forthcoming CD-ROM's. Many of the data sets are also available online electronically through computer networks; it is anticipated that as time permits, the PDS will make all the data sets that were a part of this contract available both online and on CD-ROM's.

Evans, David R.↗

Micromechanical Modeling of the Thermal Expansion of Graphite/copper Composites with Nonuniform Microstructure

Two micromechanical models were developed to investigate the thermal expansion of graphite/copper (Gr/Cu) composites. The models incorporate the effects of temperature-dependent material properties, matrix inelasticity, initial residual stresses due to processing history, and nonuniform fiber distribution. The first model is based on the multiple concentric cylinder geometry, with each cylinder treated as a two-phase composite with a characteristic fiber volume fractions. By altering the fiber volume fraction of the individual cylinders, unidirectional composites with radially nonuniform fiber distributions can be investigated using this model. The second model is based on the inelastic lamination theory. By varying the fiber content in the individual laminae, composites with nonuniform fiber distribution in the thickness direction can be investigated. In both models, the properties of the individual regions (cylinders or laminae) are calculated using the method of cells micromechanical model. Classical incremental plasticity theory is used to model the inelastic response of the copper matrix at the microlevel. The models were used to characterize the effects of nonuniform fiber distribution on the thermal expansion of Gr/Cu. These effects were compared to the effects of matrix plasticity, choice of stress-free temperature, and slight fiber misalignment. It was found that the radially nonuniform fiber distribution has little effect on the thermal expansion of Gr/Cu but could become significant for composites with large fiber-matrix transverse CTE and Young's modulus mismatch. The effect of nonuniform fiber distribution in the through-thickness direction of a laminate was more significant, but only approached that of the stress-free temperature for the most extreme cases that include large amounts of bending. Subsequent comparison with experimental thermal expansion data indicated the need for more accurate characterization of the graphite fiber thermomechanical properties. Correlation with cyclic data revealed the presence of a mechanism not considered in the developed models. The predicted response did, however, exhibit ratcheting behavior that has been observed experimentally in Gr/Cu. Finally, simulation of the actual fiber distribution of particular specimens had little effect on the predicted thermal expansion.

Bednarcyk, Brett A.↗

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing; Pattern Recognition↗

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing:Pattern Recognition↗

Enabling Dynamic Data Governance in Science: Design, Implementation, and Future Directions of the Modern Data Governance Framework

As scientific data volumes exponentially grow, dynamic, flexible and open approaches to data governance are needed. In this paper, we describe our efforts to build an open, scientific Modern Data Governance Framework (mDGF) that streamlines and makes actionable data governance requirements for projects and data providers. We present the goals and design of the mDGF. We also share our envisioned usage for the mDGF and planned future work.

Kaylin Bugbee↗

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗

A Review of Modeling Approaches for Understanding and Monitoring the Environmental Effects of Marine Renewable Energy

Understanding the environmental effects of marine energy (ME) devices is fundamental for their sustainable development and efficient regulation. However, measuring effects is difficult given the limited number of operational devices currently deployed. Numerical modeling is a powerful tool for estimating environmental effects and quantifying risks. It is most effective when informed by empirical data and coordinated with the development and implementation of monitoring protocols. We reviewed modeling techniques and information needs for six environmental stressor–receptor interactions related to ME: changes in oceanographic systems, underwater noise, electromagnetic fields (EMFs), changes in habitat, collision risk, and displacement of marine animals. This review considers the effects of tidal, wave, and ocean current energy converters. We summarized the availability and maturity of models for each stressor–receptor interaction and provide examples involving ME devices when available and analogous examples otherwise. Models for oceanographic systems and underwater noise were widely available and sometimes applied to ME, but need validation in real-world settings. Many methods are available for modeling habitat change and displacement of marine animals, but few examples related to ME exist. Models of collision risk and species response to EMFs are still in stages of theory development and need more observational data, particularly about species behavior near devices, to be effective. We conclude by synthesizing model status, commonalities between models, and overlapping monitoring needs that can be exploited to develop a coordinated and efficient set of protocols for predicting and monitoring the environmental effects of ME.

16 TIDAL AND WAVE POWER↗

Accelerator-Based Studies of Heavy Ion Interactions Relevant to Space Biomedicine

Evaluation of the effects of space radiation on the crews of long duration space missions must take into account the interactions of high energy atomic nuclei in spacecraft and planetary habitat shielding and in the bodies of the astronauts. These heavy ions (i.e. heavier than hydrogen), while relatively small in number compared to the total galactic cosmic ray (GCR) charged particle flux, can produce disproportionately large effects by virtue of their high local energy deposition: a single traversal by a heavy charged particle can kill or, what may be worse, severely damage a cell. Research into the pertinent physics and biology of heavy ion interactions has consequently been assigned a high priority in a recent report by a task group of the National Research Council. Fragmentation of the incident heavy ions in shielding or in the human body will modify an initially well known radiation field and thereby complicate both spacecraft shielding design and the evaluation of potential radiation hazards. Since it is impractical to empirically test the radiation transport properties of each possible shielding material and configuration, a great deal of effort is going into the development of models of charged particle fragmentation and transport. Accurate nuclear fragmentation cross sections (probabilities), either in the form of measurements with thin targets or theoretical calculations, are needed for input to the transport models, and fluence measurements (numbers of fragments produced by interactions in thick targets) are needed both to validate the models and to test specific shielding materials and designs. Fluence data are also needed to characterize the incident radiation field in accelerator radiobiology experiments. For a number of years, nuclear fragmentation measurements at GCR-like energies have been carried out at heavy ion accelerators including the LBL Bevalac, Saturne (France), the Synchrophasotron and Nuklotron (Dubna, Russia), SIS-18 (GSI, Germany), the Alternating Gradient Synchrotron at Brookhaven National Laboratory (BNL AGS) and the Heavy Ion Medical Accelerator (HIMAC) in Chiba, Japan. Until fairly recently most of these experiments were done to investigate fundamental problems in nuclear physics, but with the increasing interest in heavy charged particles on the part of the space flight, radiobiology and radiotherapy communities, an increasing number of experiments are being directed at these areas. Some of these measurements are discussed in references therein. Over the past several years, our group has taken cross section and fluence data at the AGS and HIMAC for several incident beams with nuclear charge, Z, between 6 and 26 at energies between 290 and 1050 MeV/nucleon. Iron (Z = 26) has been studied most extensively, since it is the heaviest ion present in significant numbers in the GCR. Targets have included tissue-equivalent and proposed shielding materials, as well as a variety of elemental targets for cross section measurements. Most of the data were taken along the beam axis, but measurements have been made off-axis, as well. Here we present selected data and briefly discuss some implications for spacecraft and planetary habitat design.

Miller, J.↗

BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA

Gene prediction has remained an active area of bioinformatics research for a long time. Still, gene prediction in large eukaryotic genomes presents a challenge that must be addressed by new algorithms. The amount and significance of the evidence available from transcriptomes and proteomes vary across genomes, between genes, and even along a single gene. User-friendly and accurate annotation pipelines that can cope with such data heterogeneity are needed. The previously developed annotation pipelines BRAKER1 and BRAKER2 use RNA-seq or protein data, respectively, but not both. A further significant performance improvement integrating all three data types was made by the recently released GeneMark-ETP. We here present the BRAKER3 pipeline that builds on GeneMark-ETP and AUGUSTUS, and further improves accuracy using the TSEBRA combiner. BRAKER3 annotates protein-coding genes in eukaryotic genomes using both short-read RNA-seq and a large protein database, along with statistical models learned iteratively and specifically for the target genome. We benchmarked the new pipeline on genomes of 11 species under an assumed level of relatedness of the target species proteome to available proteomes. BRAKER3 outperforms BRAKER1 and BRAKER2. The average transcript-level F1-score is increased by about 20 percentage points on average, whereas the difference is most pronounced for species with large and complex genomes. BRAKER3 also outperforms other existing tools, MAKER2, Funannotate, and FINDER. The code of BRAKER3 is available on GitHub and as a ready-to-run Docker container for execution with Docker or Singularity. Overall, BRAKER3 is an accurate, easy-to-use tool for eukaryotic genome annotation.

59 BASIC BIOLOGICAL SCIENCES↗

CLAS12 remote data-stream processing using ERSAP framework

Implementing a physics data processing application is relatively straightforward with the use of current containerization technologies and container image runtime services, which are prevalent in most high-performance computing (HPC) environments. However, the process is complicated by the challenges associated with data provisioning and migration, impacting the ease of workflow migration and deployment. Transitioning from traditional file-based batch processing to data-stream processing workflows is suggested as a method to streamline these workflows. This transition not only simplifies file provisioning and migration but also significantly reduces the necessity for extensive disk space. Data-stream processing is particularly effective for real-time processing during data acquisition, thereby enhancing data quality assurance. This paper introduces the integration of the JLAB CLAS12 event reconstruction application within the ERSAP data-stream processing framework that facilitates the execution of streaming event reconstruction at a remote data center and enables the return streaming of reconstructed events to JLAB while circumventing the need for temporary data storage throughout the process.

Gyurjyan, Vardan↗

Applications of Federated Learning in Semiconductor Manufacturing [Poster]

As semiconductor manufacturers explore advanced data analytics and modeling techniques and data hungry machine learning models increase in popularity due to their accuracy in solving generalized problems and ability to learn complex relationships, federated learning emerges as a privacy preserving machine learning technique for preserving data privacy and ensuring intellectual property protection. Federated Learning is a machine learning technique focused on training models using distributed data that never needs to be centrally stored, allowing the use of advanced machine learning techniques without compromising data privacy, and in the semiconductor manufacturing industry advanced machine learning techniques can reduce cost and time, but maintaining data privacy is essential to maintaining a competitive advantage. This paper systematically reviews existing literature on applications of federated learning in the semiconductor manufacturing industry with a focus on identifying common themes, algorithms, and gaps within the literature to drive future research directions. The findings reveal five key themes, including improvements in quality assurance, virtual models, privacy preservation, reliable data practices, and emerging trends and developments. By identifying key themes in literature on federated learning and semiconductor manufacturing and analyzing gaps and discussed methodologies, this study highlights several potential future research directions to expand the application of federated learning techniques in the semiconductor manufacturing domain.

42 ENGINEERING↗

High dimensional feature reduction via projection pursuit

The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many more spectral intervals than previously possible. An example of that technology is the AVIRIS system, which collects image data in 220 bands. As a result of this, new algorithms must be developed in order to analyze the more complex data effectively. Data in a high dimensional space presents a substantial challenge, since intuitive concepts valid in a 2-3 dimensional space to not necessarily apply in higher dimensional spaces. For example, high dimensional space is mostly empty. This results from the concentration of data in the corners of hypercubes. Other examples may be cited. Such observations suggest the need to project data to a subspace of a much lower dimension on a problem specific basis in such a manner that information is not lost. Projection Pursuit is a technique that will accomplish such a goal. Since it processes data in lower dimensions, it should avoid many of the difficulties of high dimensional spaces. In this paper, we begin the investigation of some of the properties of Projection Pursuit for this purpose.

Jimenez, Luis↗