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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of A Crew Health and Performance System Probabilistic Risk Assessment Tool: Proof-of-Concept Approach

The crew health and performance (CHP) system represents the span of technological interventions and tested processes and procedures that in combination address the human risk to space flight. The Human Research Program (HRP) mental model of the CHP system breaks the capabilities needed to meet NASA human flight systems standards into specific categories (i.e., countermeasures, behavioral health, medical intervention). These categories are further broken down into specific sub-groups generally associated with the human system risks that these capabilities seek to mitigate. Like the approach used to develop the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Analysis Tool (MEDPRAT), HRP tasked NASA GRC’s Cross-Cutting Computational Modeling Project with developing a CHP probabilistic risk assessment tool, the CHP-PRA. The CHP-PRA model seeks to quantify and relatively assess the human risk state within the crew health and performance domain, using a combination of knowledge about human system risks and technology and practices likely to be applied during space flight missions. This modeling system will incorporate customer and stakeholder feedback and be flexible enough to address multiple different questions about important low-level mission-specific parameters. This presentation will introduce the initial concept and development timeline for this tool and demonstrate proof-of-concept through an application addressing a specific human risk question posed within the Artemis program.

Risk analysis↗
DOE OSTI2018

ASC CSSE Level 2 Milestone #6362: Resilient Asynchronous Many Task Programming Model

This report is an outcome of the ASC CSSE Level 2 Milestone 6362: Analysis of Re- silient Asynchronous Many-Task (AMT) Programming Model. It comprises a summary and in-depth analysis of resilience schemes adapted to the AMT programming model. Herein, performance trade-offs of a resilient-AMT prograrnming model are assessed through two ap- proaches: (1) an analytical model realized by discrete event simulations and (2) empirical evaluation of benchmark programs representing regular and irregular workloads of explicit partial differential equation solvers. As part of this effort, an AMT execution simulator and a prototype resilient-AMT programming framework have been developed. The former permits us to hypothesize the performance behavior of a resilient-AMT model, and has undergone a verification and validation (V&V) process. The latter allows empirical evaluation of the perfor- mance of resilience schemes under emulated program failures and enabled the aforementioned V&V process. The outcome indicates that (1) resilience techniques implemented within an AMT framework allow efficient and scalable recovery under frequent failures, that (2) the abstraction of task and data instances in the AMT programming model enables readily us- able Application Program Interfaces (APIs) for resilience, and that (3) this abstraction enables predicting the performance of resilient-AMT applications with a simple simulation infrastruc- ture. This outcome will provide guidance for the design of the AMT programming model and runtime systems, user-level resilience support, and application development for ASC's next generation platforms (NGPs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Quantitative Analysis Guidance in Safety Software Validation

Quantitative analysis in software development has been a challenging topic over the years in safety software. While qualitative processes for vigorous safety software verification and validation (V and V) have been provided through standard such as IEEE 1012, quantitative analysis for V and V tasks such as correctness, completeness or accuracy evaluation have not been formally defined. In practice, there are quantitative analyses in terms of using software metrics. Many of these software metrics are useful in analyzing the test results. Some of them are used for providing guidance in code evaluation activities e.g. numbers of line of codes not exceeding certain limits, recursive calls are not allowed, etc. However, few can be used for providing quantitative analysis guidance for the V and V tasks such as completeness evaluation. AREVA Federal Services (AFS) has provided services for many nuclear projects in US. Through compliance with IEEE 1012, AFS V and V processes have provided vigorous qualitative processes ensuring quality level of the software products used in the project meeting the required nuclear software level. In addition, quantitative analysis is developed to provide structured validation framework ensuring 'zero defect' in the software products. This paper describes some aspects of the quantitative approaches using a sample safety application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

Strategic workload management and decision biases in aviation

Thirty pilots flew three simulated landing approaches under conditions of low, medium, and high workload. Workload conditions were created by varying time pressure and external communications requirements. Our interest was in how the pilots strategically managed or adapted to the increasing workload. We independently assessed the pilot's ranking of the priority of different discrete tasks during the approach and landing. Pilots were found to sacrifice some aspects of primary flight control as workload increased. For discrete tasks, increasing workload increased the amount of time in performing the high priority tasks, decreased the time in performing those of lowest priority, and did not affect duration of performance episodes or optimality of scheduling of tasks of any priority level. Individual differences analysis revealed that high-performing subjects scheduled discrete tasks earlier in the flight and shifted more often between different activities.

Raby, Mireille↗
DOE OSTI2011

Data-intensive management and analysis for scientifc simulations.

Scientific simulations can produce enormous amounts of data, making the analysis of results and management of files a difficult task for scientists. The simulation management and analysis system (Smaash) described here is designed to allow scientists to easily capture, store, organize, monitor, and analyze simulation results. The system is automatic, standardized, and secure. Smaash was built using open-source tools and modularized to be independent of the scientific simulation. The web-based front-end allows the scientist to easily interact with the data, and has proved its usefulness in improving the efficiency of a scientific team's workflow. High performance parallel computing allows scientists to solve complex physical problems through computer simulation. However, the massive amounts of data generated and the complex computing environment can create additional complications. A recent review by Ludaescher et al.(2009) describes how scientific workflows can assist scientists in extracting knowledge from these data-intensive operations by automating components within pipelines. Within the fusion community, Klasky et al.(2008) and colleagues have developed a system that handles the storage management, data movement, metadata generation and management, and a means to analyze the results. In response to scientists needs, a simulation management and analysis system (Smaash) was developed at the University of Chicago and Argonne National Laboratory (USA). Smaash provides an integrated way to monitor simulations and analyze computational results; catalog, store, and retrieve simulations; and prepare output for publications. The system is independent of the particular simulation code, accessible from many HPC and browser-based platforms, and built around open-source software tools. Data security and provenance is considered throughout. The analysis components are hidden behind a web-based front end, enabling scientists to focus on their results and not get bogged down by information overload.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

A novel vacuum spectrometer for total reflection x-ray fluorescence analysis with two exchangeable low power x-ray sources for the analysis of low, medium, and high Z elements in sequence

The extension of the detectable elemental range with Total Reflection X-ray Fluorescence (TXRF) analysis is a challenging task. In this paper, it is demonstrated how a TXRF spectrometer is modified to analyze elements from carbon to uranium. Based on the existing design of a vacuum TXRF spectrometer with a 12 specimen sample changer, the following components were renewed: the silicon drift detector with 20 mm{sup 2} active area and having a special ultra-thin polymer window allowing the detection of elements from carbon upwards. Two exchangeable X-ray sources guarantee the efficient excitation of both low and high Z elements. These X-ray sources were two light-weighted easily mountable 35 W air-cooled low-power tubes with Cr and Rh anodes, respectively. The air cooled tubes and the Peltier-cooled detector allowed to construct a transportable tabletop spectrometer with compact dimensions, as neither liquid nitrogen cooling for the detector nor a water cooling circuit and a bulky high voltage generator for the X-ray tubes are required. Due to the excellent background conditions as a result of the TXRF geometry, detection limits of 150 ng for C, 12 ng for F, and 3.3 ng for Na have been obtained using Cr excitation in vacuum. For Rh excitation, the detection limits of 90 pg could be achieved for Sr. Taking 10 to 20 μl of sample volume, extrapolated detection limits in the ng/g (ppb) range are resulting in terms of concentration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia

Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging. Here in this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel machine for detecting higher order interactions among biologically relevant multimodal data. Using a semiparametric method on a reproducing kernel Hilbert space, we formulated the proposed method as a standard mixed-effects linear model and derived a score-based variance component statistic to test higher order interactions between multimodal datasets. The method was evaluated using extensive numerical simulation and real data from the Mind Clinical Imaging Consortium with both schizophrenia patients and healthy controls. Our method identified 13-triplets that included 6 gene-derived SNPs, 10 ROIs, and 6 gene-specific DNA methylations that are correlated with the changes in hippocampal volume, suggesting that these triplets may be important for explaining schizophrenia-related neurodegeneration. The performance of the proposed method is compared with the following methods: test based on only first and first few principal components followed by multiple regression, and full principal component analysis regression, and the sequence kernel association test. With strong evidence (p-value ≤0.000001), the triplet (MAGI2, CRBLCrus1.L, FBXO28) is a significant biomarker for schizophrenia patients. This novel method can be applicable to the study of other disease processes, where multimodal data analysis is a common task.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We develop a tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3000 (>9500) phosphopeptides from 1 (10) µg of cell lysate using the label-free method without a spectral library. It also enables precise quantification of ~600 phosphopeptides from 100 sorted cells (single-cell level input for the enriched phosphopeptides) and ~700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 µm (equivalent to ~100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

OrfM: a fast open reading frame predictor for metagenomic data

Finding and translating stretches of DNA lacking stop codons is a task common in the analysis of sequence data. However, the computational tools for finding open reading frames are sufficiently slow that they are becoming a bottleneck as the volume of sequence data grows. This computational bottleneck is especially problematic in metagenomics when searching unassembled reads, or screening assembled contigs for genes of interest. Here, we present OrfM, a tool to rapidly identify open reading frames (ORFs) in sequence data by applying the Aho–Corasick algorithm to find regions uninterrupted by stop codons. Benchmarking revealed that OrfM finds identical ORFs to similar tools (‘GetOrf’ and ‘Translate’) but is four-five times faster. While OrfM is sequencing platform-agnostic, it is best suited to large, high quality datasets such as those produced by Illumina sequencers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Mapping and controlling ultrafast dynamics of highly excited H 2 molecules by VUV-IR pump-probe schemes

Here, we used ultrashort femtosecond vacuum ultraviolet (VUV) and infrared (IR) pulses in a pump-probe scheme to map the dynamics and nonequilibrium dissociation channels of excited neutral H 2 molecules. A nuclear wave packet is created in the B 1 Σ$+\atop{u}$ state of the neutral H 2 molecule by absorption of the ninth harmonic of the driving infrared laser field. Due to the large stretching amplitude of the molecule excited in the B 1 Σ$+\atop{u}$ electronic state, the effective H 2 + ionization potential changes significantly as the nuclear wave packet vibrates in the bound, highly electronically and vibrationally excited B potential-energy curve. We probed such dynamics by ionizing the excited neutral molecule using time-delayed VUV-or-IR radiation. We identified the nonequilibrium dissociation channels by utilizing three-dimensional momentum imaging of the ion fragments. We also found that different dissociation channels can be controlled, to some extent, by changing the IR laser intensity and by choosing the wavelength of the probe laser light. Furthermore, we concluded that even in a benchmark molecular system such as H 2 *, the interpretation of the nonequilibrium multiphoton and multicolor ionization processes is still a challenging task, requiring intricate theoretical analysis.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application-specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. Here, we present the software-defined accelerator (SODA) synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multilevel representations to progressively lower and optimize the input code. Our approach does not require the application developer to write any register-transfer level code, and it is able to reach up to 364 giga floating point operations per second (GFLOPS)/W efficiency (32-bit precision) on typical convolutional neural network operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗
DOE OSTI2016

Net Shape Fabricated Low Cost MHK Pass-Through the Hub Turbine Blades with Integrated Health Management Technology

The primary objective of this project is to develop a three-blade MHK rotor with low manufacturing and maintenance costs. The proposed program will design, fabricate and test a novel half-scale low cost, net shape fabricated single piece three-blade MHK rotor with integrated health management technology to demonstrate significant Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) cost reductions due to the novel design and manufacturing process. The proposed project is divided into three major tasks: Task 1: Single Piece Three-blade Kinetic Hydropower System (KHPS) Rotor Full-Scale and Half-Scale Design; Task 2: Composite Manufacturing Trials and Half-Scale Prototype Rotor Fabrication; and Task 3: Material Characterization and Half-Scale Prototype Test and Evaluation. These three tasks include design and analysis of full-scale and half-scale three-blade rotor prototypes using computational fluid dynamics (CFD) and finite-element analysis (FEA), demonstration of a novel half-scale net shape fabrication process, determination of a fatigue threshold composite strain allowable, three-blade rotor mold design, manufacture of half-scale rotor clam shell mold, three-blade rotor test fixture design and fabrication, development of final manufacturing and test plans, manufacture of the half-scale net shape composite single blade and three-blade prototypes, and test and evaluation of the half-scale rotor.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists

Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data, identifying patterns and making decisions with minimal human intervention can be extremely useful to their business (e.g., image classification, recommending a product to a customer, finding friends in a social network, predicting customers actions, etc.). These success stories have been motivating scientists who study physics, chemistry, materials, medicine, and many other subjects, to explore a new pathway of utilizing machine learning techniques like regression and classification for their scientific activities. However, most existing machine learning tools, systems, and methodologies have been developed for programming experts but not for scientists (or any users) who have no or little knowledge of programming. ASCENDS is a toolkit that is developed to assist scientists (or any persons) who want to use their data for machine learning tasks, more specifically, correlation analysis, regression, and classification. ASCENDS does not require programming skills. Instead, it provides a set of simple but powerful CLI (Command Line Interface) and GUI (Graphic User Interface) tools for non-data scientists to be able to intuitively perform advanced data analysis and machine learning techniques. ASCENDS has been implemented by wrapping around opensource software including Keras, TensorFlow, and scikit-learn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

DESIGN STUDY FOR A LOW-ENRICHED URANIUM CORE FOR THE HIGH FLUX ISOTOPE REACTOR, ANNUAL REPORT FOR FY 2010

This report documents progress made during FY 2010 in studies of converting the High Flux Isotope Reactor (HFIR) from high enriched uranium (HEU) fuel to low enriched uranium (LEU) fuel. Conversion from HEU to LEU will require a change in fuel form from uranium oxide to a uranium-molybdenum alloy. With axial and radial grading of the fuel foil and an increase in reactor power to 100 MW, calculations indicate that the HFIR can be operated with LEU fuel with no degradation in performance to users from the current level. Studies are reported of support to a thermal hydraulic test loop design, the implementation of finite element, thermal hydraulic analysis capability, and infrastructure tasks at HFIR to upgrade the facility for operation at 100 MW. A discussion of difficulties with preparing a fuel specification for the uranium-molybdenum alloy is provided. Continuing development in the definition of the fuel fabrication process is described.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Energy Saving Glass Lamination via Selective Radio Frequency Heating

This project focused on advancing radio-frequency (RF) lamination technology closer to commercial implementation, in order to reduce the energy intensity of glass lamination by up to 90%. Lamination comprises a wide range of products including autoglass, architectural safety and innovative design glass, transparent armor (e.g. bullet proof glass), smart glass, mirrors, and encapsulation of photovoltaics. Lamination is also the fastest growing segment of glass manufacturing, with photovoltaics, architectural needs, and an anticipated transition to laminated side windows in vehicles. The state-of-the-art for glass lamination is to use autoclaves, which apply heat and uniform gas pressure to bond the laminates over the course of 1 to 18 hours. Laminates consist of layers of glass or other materials bonded with vinyl or urethane interlayers. In autoclaving, significant heat energy is lost heating the chamber, pressurized air, glass racks, and the glass. In RF lamination, the heat is generated directly in the vinyl interlayer, causing it to heat and melt quickly, in just 1 to 10 minutes, without significantly heating the glass or the equipment. The main purpose of this project was to provide evidence that low energy, rapid RF lamination quality met the same standards as conventionally autoclaved windows. The development of concepts for laminating curved glass with RF lamination was a major goal. Other primary goals included developing a stronger understanding of the lamination product markets described above, and to refine the potential benefits of commercial implementation. The scope of the project was to complete implementation concept studies in preparation for continuation into advanced development, pilot studies, and commercial implementation. The project consisted of 6 main tasks. The first dealt with lamination with poly-vinyl butyral (PVB) interlayers, which prior work had shown difficulties in achieving good quality laminates, working with Pilkington North America. The second task dealt with a study of current lamination processes in the various laminate industries, and development of concepts for integrating RF lamination into new or existing processes. The third task explored the use of a non-destructive technique for analyzing laminate adhesion with the University of Illinois at Urbana-Champaign. The fourth task focused on developing concepts for curved glass lamination using RF lamination. The fifth and sixth tasks together comprised an analysis of laminate product markets, ranking for applicability and commercialization potential, and the development of commercialization strategies for those products. In addition, throughout the project as new experimental data and conventional process data were obtained, the benefits analysis of RF lamination was refined. The goals of the project described above were achieved, positioning RF lamination for the next stage growth envisioned in the original Industrial Grand Challenge proposal. Working with Pilkington North America, lamination of flat autoglass with PVB was achieved, meeting all 16 stringent industry tests. In particular, PVB laminates made with RF lamination passed environmental tests including the high temperature, 120 C bake test, without significant formation of bubbles (defects). The adhesion of PVB to glass was measured using the pummel method. Adhesion values ranging from 1 to 7 out of 10 were obtained. The significant process parameters affecting the environmental and adhesion performance were identified through a designed experiment. Pre-lamination process variables including PVB storage humidity and the de-airing process (vacuum or nip rolling) were significant, as well as the level of pressure applied to the laminate during the RF process. Analysis of manufacturing with RF lamination equipment, based on the processes developed indicated that 3 RF presses could replace a typical auto-industry autoclave to achieve equal or greater throughput with possibly less capital cost and smaller footprint. Concepts for curved lamination identifying castable molds for prototyping were developed, which allowed Ceralink to obtain commitment to begin curved tooling development. The project significantly helped to advance RF lamination past the feasibility and novelty stage and into the realm of commercial acceptance as a viable alternative to autoclaves. The demonstration of autoclave-quality autoglass produced in just 1 minute with RF lamination, with validation by Pilkington, has fueled industry motivation to seriously consider RF lamination. The industry and other contacts and outreach made in the study of laminate markets (including 3 technical publications and 5 conference presentations), has resulted in a recent surge in RF lamination activity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Energy Saving Glass Lamination via Selective Radio Frequency Heating

This project focused on advancing radio-frequency (RF) lamination technology closer to commercial implementation, in order to reduce the energy intensity of glass lamination by up to 90%. Lamination comprises a wide range of products including autoglass, architectural safety and innovative design glass, transparent armor (e.g. bullet proof glass), smart glass, mirrors, and encapsulation of photovoltaics. Lamination is also the fastest growing segment of glass manufacturing, with photovoltaics, architectural needs, and an anticipated transition to laminated side windows in vehicles. The state-of-the-art for glass lamination is to use autoclaves, which apply heat and uniform gas pressure to bond the laminates over the course of 1 to 18 hours. Laminates consist of layers of glass or other materials bonded with vinyl or urethane interlayers. In autoclaving, significant heat energy is lost heating the chamber, pressurized air, glass racks, and the glass. In RF lamination, the heat is generated directly in the vinyl interlayer, causing it to heat and melt quickly, in just 1 to 10 minutes, without significantly heating the glass or the equipment. The main purpose of this project was to provide evidence that low energy, rapid RF lamination quality met the same standards as conventionally autoclaved windows. The development of concepts for laminating curved glass with RF lamination was a major goal. Other primary goals included developing a stronger understanding of the lamination product markets described above, and to refine the potential benefits of commercial implementation. The scope of the project was to complete implementation concept studies in preparation for continuation into advanced development, pilot studies, and commercial implementation. The project consisted of 6 main tasks. The first dealt with lamination with poly-vinyl butyral (PVB) interlayers, which prior work had shown difficulties in achieving good quality laminates, working with Pilkington North America. The second task dealt with a study of current lamination processes in the various laminate industries, and development of concepts for integrating RF lamination into new or existing processes. The third task explored the use of a non-destructive technique for analyzing laminate adhesion with the University of Illinois at Urbana-Champaign. The fourth task focused on developing concepts for curved glass lamination using RF lamination. The fifth and sixth tasks together comprised an analysis of laminate product markets, ranking for applicability and commercialization potential, and the development of commercialization strategies for those products. In addition, throughout the project as new experimental data and conventional process data were obtained, the benefits analysis of RF lamination was refined. The goals of the project described above were achieved, positioning RF lamination for the next stage growth envisioned in the original Industrial Grand Challenge proposal. Working with Pilkington North America, lamination of flat autoglass with PVB was achieved, meeting all 16 stringent industry tests. In particular, PVB laminates made with RF lamination passed environmental tests including the high temperature, 120°C bake test, without significant formation of bubbles (defects). The adhesion of PVB to glass was measured using the pummel method. Adhesion values ranging from 1 to 7 out of 10 were obtained. The significant process parameters affecting the environmental and adhesion performance were identified through a designed experiment. Pre-lamination process variables including PVB storage humidity and the de-airing process (vacuum or nip rolling) were significant, as well as the level of pressure applied to the laminate during the RF process. Analysis of manufacturing with RF lamination equipment, based on the processes developed indicated that 3 RF presses could replace a typical auto-industry autoclave to achieve equal or greater throughput with possibly less capital cost and smaller footprint. Concepts for curved lamination identifying castable molds for prototyping were developed, which allowed Ceralink to obtain commitment to begin curved tooling development. The project significantly helped to advance RF lamination past the feasibility and novelty stage and into the realm of commercial acceptance as a viable alternative to autoclaves. The demonstration of autoclave-quality autoglass produced in just 1 minute with RF lamination, with validation by Pilkington, has fueled industry motivation to seriously consider RF lamination. The industry and other contacts and outreach made in the study of laminate markets (including 3 technical publications and 5 conference presentations), has resulted in a recent surge in RF lamination activity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

RolX: Role Extraction and Mining in Large Networks

Given a graph, how can we automatically discover roles for nodes? Roles could be, eg., ’bridges’, or ’periphery-nodes’, etc. Roles are compact summaries of a node’s behavior that generalize across networks. They enable numerous novel and useful network mining tasks, such as sense-making, searching for similar nodes, and node classification. We propose RolX (Role eXtraction), a scalable (linear in the number of edges), unsupervised learning approach for automatically extracting roles from general network data. We demonstrate the effectiveness of RolX on several network mining tasks, from exploratory data analysis to network transfer learning. Moreover, we compare network role discovery with network community discovery. We highlight fundamental differences between the two (e.g., roles generalize across disconnected networks, communities do not).

97 MATHEMATICS AND COMPUTING↗