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Vehicle Lightweighting: Mass Reduction Spectrum Analysis and Process Cost Modeling
The U.S. Department of Energy’s Vehicle Technologies Office, Materials area commissioned a study to model and assess manufacturing economics of alternative design and production strategies for a series of lightweight vehicle concepts. In the first two phases of this effort examined combinations of strategies aimed at achieving strategic targets of 40% and a 45% mass reduction relative to a standard North American midsize passenger sedan at an effective cost of $3.42 per pound (lb) saved. These results have been reported in the Idaho National Laboratory report INL/EXT-14-33863 entitled Vehicle Lightweighting: 40% and 45% Weight Savings Analysis: Technical Cost Modeling for Vehicle Lightweighting published in March 2015. The data for these strategies were drawn from many sources, including Lotus Engineering Limited and FEV, Inc. lightweighting studies, U.S. Department of Energy-funded Vehma International of America, Inc./Ford Motor Company Multi-Material Lightweight Prototype Vehicle Demonstration Project, the Aluminum Association Transportation Group, many United States Council for Automotive Research’s/United States Automotive Materials Partnership LLC lightweight materials programs, and IBIS Associates, Inc.’s decades of experience in automotive lightweighting and materials substitution analyses.
Charge-exchange coupling between pickup ions across the heliopause and its effect on energetic neutral hydrogen flux
Pickup ions (PUIs) appear to play an integral role in the multi-component nature of the plasma in the interaction between the solar wind (SW) and local interstellar medium (LISM). Three-dimensional (3D) MHD simulations with a kinetic treatment for neutrals and PUIs are currently still not viable. In light of recent energetic neutral atom (ENA) observations by the Interstellar Boundary EXplorer, the purpose of this paper is to illustrate the complex coupling between PUIs across the heliopause (HP) as facilitated by ENAs using estimates of PUI properties extracted from a 3D MHD simulation of the SW-LISM interaction with kinetic neutrals. First, we improve upon the multi-component treatment of the inner heliosheath (IHS) plasma from Zank et al. by including the extinction of PUIs through charge-exchange. We find a significant amount of energy is transferred away from hot, termination shock-processed PUIs into a colder, 'freshly injected' PUI population. Second, we extend the multi-component approach to estimate ENA flux from the outer heliosheath (OHS), formed from charge-exchange between interstellar hydrogen atoms and energetic PUIs. These PUIs are formed from ENAs in the IHS that crossed the HP and experienced charge-exchange. Our estimates, based on plasma-neutral simulations of the SW-LISM interaction and a post-processing analysis of ENAs and PUIs, suggest the majority of flux visible at 1 AU from the front of the heliosphere, between ∼0.02 and 10 keV, originates from OHS PUIs, indicating strong coupling between the IHS and OHS plasmas through charge-exchange.
Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes
Not Available
Process Image Analysis using Big Data, Machine Learning, and Computer Vision
The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.
Energy Systems Process Modeling, Analysis, and Experiment Design [Slides]
This presentation is to be used in Feynman Center outreach discussions. It describes public information about some Los Alamos interests and activities in modeling and analysis in energy systems including carbon capture and direct air capture. In particular this addresses the CCSI2 project’s open-source toolkit and ongoing partnerships, as well as summarizing the published Feynman Center capability snapshot on direct air capture.
Nuclear Criticality Safety Process Hazard Analysis for General Machining
A hazard analysis has been requested from Nuclear Criticality Safety (NCS) regarding the identification of normal and credible abnormal conditions relative to machining activities performed at NMCA location UMPETY in Room SQUAT of SHANGRALA.
X-Ray Scattering Data Processing and Analysis
Semicrystalline polymers have a degree of crystallinity that depends on chain structure and crystallization conditions. Thermomechanical properties are influenced by the degree of crystallinity and crystalline morphology. A common method used to understand crystalline content, crystal and amorphous layer thickness, and layer thickness distributions, is X-ray scattering (XS). This report uses XS to first investigate crystalline orientation in high density polyethylene (HDPE) samples. Then, a single orientation is analyzed via XS in a temperature study to investigate crystalline behavior under changing temperatures. Lastly, block copolymer filaments extruded at varying speeds are analyzed. The X-ray data are used to gain a baseline understanding of crystalline behavior in these unique filaments.
A New Approach for Feature Event and Process (FEP) Analysis of UNF/HLW Disposal - Slides.
Abstract not provided.
Failure Analysis and Process Improvement for Superconducting Electronics.
Abstract not provided.
High-throughput Micro-analytical Sample Generation and Analysis of Process Salts
Explore the source record for details and available documents.
Failure Analysis and Process Verification of High Density Copper ICs.
Abstract not provided.
Failure Analysis and Process Verification of High Density Copper ICs Used in Multi-Chip Modules (MCM).
Abstract not provided.
Systems and methods for estimation and prediction of battery health and performance
Systems and computer-implemented methods are used for analyzing battery information. The battery information may be acquired from both passive data acquisition and active data acquisition. Active data may be used for feature extraction and parameter identification responsive to the input data relative to an electrical equivalent circuit model to develop geometric-based parameters and optimization-based parameters. These parameters can be combined with a decision fusion algorithm to develop internal battery parameters. Analysis processes including particle filter analysis, neural network analysis, and auto regressive moving average analysis can be used to analyze the internal battery parameters and develop battery health metrics. Additional decision fusion algorithms can be used to combine the internal battery parameters and the battery health metrics to develop state-of-health estimations, state-of-charge estimations, remaining-useful-life predictions, and end-of-life predictions for the battery.
The 2018 Dynamic Networks Data Processing and Analysis Experiment (DNE18).
Abstract not provided.