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At least 1,639 records · Page 91

Volume Imaging & Tracking Radar Open Research Topics

The Volume Imaging & Tracking Radar (VITR) is a multistatic broadband system designed to track multiple centimeter sized objects whose velocities exceed 1 km/s. The VITR characteristics are: Multistatic, multiple transmitters & receivers; Spatially diverse & aperiodic: The transmitting and receiving antennas may be arbitrarily located; Pulsed, broad band (6-13 GHz); Time-domain; One pulse in the air at a time; No carrier; Returns digitized, processed & analyzed at RF frequencies. The data products are: Three dimensional object of interest (OOI) tracks; Multistatic Doppler velocity estimates of the OOIs; Evolution of radar cross-section (RCS) as a function of time along the track; Volume movies (three spatial dimensions and time) of the OOIs; Bistatic inverse synthetic aperture radar (ISAR) processing.

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Influence of Diffusional Surface Alloying on the Hardened-Layer Thickness for Gray-Iron Machine Parts

In diffusional surface alloying, gray-iron components of vehicles and machines are heated in contact with oxides of the alloying elements (chromium, titanium, vanadium, and molybdenum). The influence of the sample temperature and holding time in diffusional surface alloying on the thickness of the hardened layer is investigated, on the basis of experiment planning. The models obtained may be used to ensure specified thickness of the hardened layer in diffusional surface alloying, with maximum productivity in both production and repair processes.

36 MATERIALS SCIENCE↗

Articulating feedstock delivery device

A fully articulable feedstock delivery device that is designed to operate at pressure and temperature extremes. The device incorporates an articulating ball assembly which allows for more accurate delivery of the feedstock to a target location. The device is suitable for a variety of applications including, but not limited to, delivery of feedstock to a high-pressure reaction chamber or process zone.

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Process Optimization

Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use in powder-bed fusion and directed energy deposition processes. In the latter case, closed-loop feedback is used to control melt pool temperature and cooling rate in order to achieve desired microstructure.

Sprayberry, Michael↗

Utilizing the Shift Technical Engineer Pipeline to Develop the Next Generation of Engineers - 17354

As the liquid waste contractor for the U.S. Department of Energy's (DOE) Savannah River Site (SRS), Savannah River Remediation (SRR) is responsible for safely treating and dispositioning approximately 35 million gallons of liquid waste stored at SRS. To achieve this mission, SRR manages and operates several complex nuclear facilities. These nuclear facilities include the H and F Tank Farms, the Defense Waste Processing Facility (DWPF), and the Saltstone Processing and Disposal Facility. To support the operations of these complex nuclear facilities, a Shift Technical Engineer (STE) is stationed for every shift. The STE is the sole Engineering Organization representative on-shift and serves as a direct technical resource for operations, including safety basis interpretation, process monitoring and prompt troubleshooting support. The training and qualification for an STE is more intensive than for typical technical staff personnel at SRR, involving additional classes, under-instruction watches, demonstration of practical factors, and culminating in an intense oral board examination. Like many other contractors in the DOE complex, SRR faces the challenge of preparing a significant number of new generation engineers to take the place of an aging workforce. Beyond the traditional training to establish minimum technical qualifications, SRR has established a number of initiatives aimed at accelerating the process of preparing early career engineers to replace experienced senior engineers. These initiatives include an internal rotational program, technical exchange activities with companies at other DOE sites, and an STE pipeline. The STE role provides a unique mechanism for select, early career engineers to gain in-depth knowledge and significant responsibility normally not achieved until much later in their careers. Once qualification is complete, the engineers perform the STE duties, providing technical support for nuclear facility operations. In addition, creating an STE pipeline, where promising young engineers are continually being qualified to replace the on-shift STEs, provides the company with a source of experienced engineers with in-depth technical knowledge as well as valuable experience interfacing with operations and other facility support groups. This paper will discuss the STE position, the qualification process, and how SRR is using the STE qualification pipeline to benefit both the company and the individual engineer. (authors)

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Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

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In Situ Decommissioning (ISD) Concepts and Approaches for Excess Nuclear Facilities Decommissioning End State - 13367

The United States Department of Energy (DOE) currently has numerous radiologically contaminated excess nuclear facilities waiting decommissioning throughout the Complex. The traditional decommissioning end state is complete removal. This commonly involves demolishing the facility, often segregating various components and building materials and disposing of the highly contaminated, massive structures containing tons of highly contaminated equipment and piping in a (controlled and approved) landfill, at times hundreds of miles from the facility location. Traditional demolition is costly, and results in significant risks to workers, as well as risks and costs associated with transporting the materials to a disposal site. In situ decommissioning (ISD or entombment) is a viable alternative to demolition, offering comparable and potentially more protective protection of human health and the environment, but at a significantly reduced cost and worker risk. The Savannah River Site (SRS) has completed the initial ISD deployment for radiologically contaminated facilities. Two reactor (P and R Reactors) facilities were decommissioned in 2011 using the ISD approach through the American Recovery and Reinvestment Act. The SRS ISD approach resolved programmatic, regulatory and technical/engineering issues associated with avoiding the potential hazards and cost associated with generating and disposing of an estimated 124,300 metric tons (153,000 m{sup 3}) of contaminated debris per reactor. The DOE Environmental Management Office of Deactivation and Decommissioning and Facility Engineering, through the Savannah River National Laboratory, is currently investigating potential monitoring techniques and strategies to assess ISD effectiveness. As part of SRS's strategic planning, the site is seeking to leverage in situ decommissioning concepts, approaches and facilities to conduct research, design end states, and assist in regulatory interactions in broad national and international government and private industry decommissioning applications. SRS offers critical services based upon the SRS experience in decommissioning and reactor entombment technology (e.g., grout formulations for varying conditions, structural and material sciences). The SRS ISD approach follows a systems engineering framework to achieve a regulatory acceptable end state based on established protocols, attains the final end state with minimal long stewardship requirements, protects industrial workers, and protects groundwater and the environment. The ISD systems engineering framework addresses key areas of the remedial process planning, technology development and deployment, and assessment to attain the ultimate goal of natural resource stewardship and protecting the public. The development and deployment of the SRS ISD approach has established a path for ISD of other large nuclear facilities in the United States and around the globe as an acceptable remedial alternative for decommissioning nuclear facilities. (authors)

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Hanford Surface Barrier Design Guidance

This status report presents results of progress made during fiscal year 2019 towards developing a software tool for designing surface barriers in the Central Plateau. This tool is intended to be used to support feasibility studies and remedy applications. This status report summarizes the methodology followed to develop preliminary vadose zone reduced order models (VZ-ROMs) for use in such a tool. The ROM development process required generation of a training and testing dataset representing an example waste site in the Central Plateau. This training data was prepared via eSTOMP simulations that simulated variable drainage through hypothetical surface barriers into waste sites within the Central Plateau. Prior to regression analysis, these numerical results were analyzed to understand the behavior of contaminant solutes under different drainage conditions in the vadose zone. Results from eSTOMP simulations provided an understanding of the effectiveness of hypothetical surface barriers in isolating the subsurface system and mitigating contaminant transport. The primary objective of the work was to establish an appropriate ROM methodology. Further development is required to adapt the ROMs presented here to appropriately couple surface barrier construction design. Future iterations will be used to predict the performance of different surface barrier engineering designs. Future development will follow a similar process to the one demonstrated in this document.

54 ENVIRONMENTAL SCIENCES↗

An empirical investigation of organic software product lines

Abstract Software product line engineering is a best practice for managing reuse in families of software systems that is increasingly being applied to novel and emerging domains. In this work we investigate the use of software product line engineering in one of these new domains, synthetic biology. In synthetic biology living organisms are programmed to perform new functions or improve existing functions. These programs are designed and constructed using small building blocks made out of DNA. We conjecture that there are families of products that consist of common and variable DNA parts, and we can leverage product line engineering to help synthetic biologists build, evolve, and reuse DNA parts. In this paper we perform an investigation of domain engineering that leverages an open-source repository of more than 45,000 reusable DNA parts. We show the feasibility of these new types of product line models by identifying features and related artifacts in up to 93.5% of products, and that there is indeed both commonality and variability. We then construct feature models for four commonly engineered functions leading to product lines ranging from 10 to 7.5 × 10 20 products. In a case study we demonstrate how we can use the feature models to help guide new experimentation in aspects of application engineering. Finally, in an empirical study we demonstrate the effectiveness and efficiency of automated reverse engineering on both complete and incomplete sets of products. In the process of these studies, we highlight key challenges and uncovered limitations of existing SPL techniques and tools which provide a roadmap for making SPL engineering applicable to new and emerging domains.

97 MATHEMATICS AND COMPUTING↗

Achieving high strength and ductility in traditionally brittle soft magnetic intermetallics via additive manufacturing

Intermetallic alloys possess exceptional soft magnetic properties, including high permeability, low coercivity, and high saturation induction, but exhibit poor mechanical properties that make them impractical to bulk process and use at ideal compositions. We used laser-based Additive Manufacturing to process traditionally brittle Fe–Co and Fe–Si alloys in bulk form without macroscopic defects and at near-ideal compositions for electromagnetic applications. The binary Fe–50Co, as a model material, demonstrated simultaneous high strength (600–700 MPa) and high ductility (35%) in tension, corresponding to a ~300% increase in strength and an order-of-magnitude improvement in ductility relative to conventionally processed material. Atomic-scale toughening and strengthening mechanisms, based on engineered multiscale microstructures, are proposed to explain the unusual combination of mechanical properties. Here, this work presents an instance in which metal Additive Manufacturing processes are enabling, rather than limiting, the development of higher-performance alloys.

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Engineering-scale Modeling of High-Temperature Creep and Creep Crack Growth in Alloy 316H

This document demonstrates completion of the goals described in the technical narrative of the Department of Energy’s Industry Funding Opportunity Announcement (iFOA) project entitled “Modeling and Simulation Development Pathways to Accelerating KP-FHR Licensing,” which relates to the development and demonstration of capabilities for conducting engineering-scale simulations of Alloy 316H components under high-temperature conditions. This work encompassed two major aspects: integrating and testing constitutive models for the creep response of 316H at high temperatures, and developing tools for modeling creep crack growth (CCG) in 316H. Two classes of constitutive models were used in this effort: phenomenological models based on behavior observed at the engineering scale, and reduced-order models (ROMs) that represent the nonlinear response of mesoscale models that capture the sensitivity to material microstructure and processing. Likewise, the approaches employed for CCG modeling considered both simplified engineering approaches and detailed simulations of creep and damage ahead of the crack tip. These developments, which were performed by utilizing the Grizzly code as well as the open-source libraries it depends on, strengthen Grizzly’s ability to support licensing and safety analyses of high-temperature reactor components.

316H↗

Fundamental insights on ignition and combustion of natural gas in an active fueled pre-chamber spark-ignition system

Pre-chamber spark-ignition (PCSI), either fueled or non-fueled, is a leading concept with the potential to enable diesel-like efficiency in medium-duty (MD) and heavy-duty (HD) natural gas (NG) engines. However, the inadequate scientific base and simulation tools to describe/predict the underlying processes governing PCSI systems is one of the key barriers to market penetration of PCSI for MD/HD NG engines. To this end, experiments were performed in a heavy-duty, optical, single-cylinder engine fitted with an active fueled PCSI module. Furthermore, the spatial and temporal progress of ignition and subsequent combustion of lean-burn natural gas using PCSI system were studied using optical diagnostic imaging and heat release analysis based on main-chamber and pre-chamber pressure measurements.

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Cooperative Research and Development Agreement among National Energy Technology Laboratory, The Board of Regents of the University System of Georgia by and on behalf of Georgia Institute of Technology, and University of Texas at El Paso [Abstract]

Georgia Institute of Technology (GIT), University of Texas at El Paso (UTEP), and the National Energy Technology Laboratory (NETL) will collaborate and develop cyber-physical systems for advanced power systems. GIT will test virtual models on hybrid power system hardware and cyber physical components. UTEP will test novel actuators on hybrid power system hardware. NETL will access GIT’s expertise in the engineering and real time simulation of power system processes for cyber-physical systems and simulations to control hardware. NETL will establish a relationship to promote UTEP’s capabilities in additive manufacturing and high-temperature piezo-electric devices with the potential for controlling high-temperature flows with a light and inexpensive device at high response rates. This project is the result of an EERE Advanced Manufacturing Office open Multi-Topic awarded proposal led by GIT titled, “Robust Combined Heat and Hybrid Power (CHHP) for High Electrical Efficiency Cogeneration”.

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In situ probing of structure and deagglomeration of SnO 2 colloids via small-angle X-ray scattering

Transforming dry nanopowders into stable colloidal dispersions remains challenging due to the cohesive forces between the nanoparticles (NPs) which promote agglomeration. Effective dispersion and deagglomeration of these agglomerates is a critical process in the formulation and preparation of nanoparticle-based functional materials via the colloidal route. Understanding the deagglomeration dynamics provides information to improve microstructural quality in various applications by enabling engineering of agglomerate size, structure and morphology. However, the deagglomeration process dynamics with respect to the evolution of the fractal agglomerate structures, particularly for very small NPs, is still poorly understood and requires further investigation. This study employs in situ small-angle X-ray scattering (SAXS) to investigate the sonication-induced deagglomeration of SnO 2 NPs. Electrostatically stabilized SnO 2 colloids with varying primary particle size (6–21 nm) are investigated in a specifically designed in situ cell using synchrotron-based SAXS to study the influence of sonication time and intensity on the nanoscaled agglomerates. Complete structural analysis via SAXS reveals a direct correlation between changes in agglomerate size and structure, size-dependent deagglomeration behavior and a dependence on the overall energy introduced during sonication into the dispersion regardless of the actual power as well as ultrasonic process parameters in case of SnO 2 NPs. The results suggest that control of the dispersion process during ultrasonic deagglomeration results in tailoring agglomerates with respect to size and structure.

Deagglomeration↗

Development of Alternative Vacuum Pumps for Tritium Service

In tritium process systems, vacuum pumps are typically used to evacuate volumes and piping, as well as transfer gas to other parts of the process. This was done using the combination of an all-metal scroll pump with a metal bellows backing pump. The all-metal scroll pump, manufactured by Normetex, has been unavailable since 2012, and efforts continue to find a suitable replacement. The main obstacle is finding a pump that has no oils or polymer components, which degrade when exposed to tritium and introduce corrosive and/or hazardous impurities into the process. Since turbomolecular pumps are used in tritium processing, it is thought that pumps similar to the turbomolecular pumps would be of interest. The pumps would need to operate at lower rotational speeds to handle higher pressures and flow rates, which is best suited for Molecular Drag Pumps (MDP). To determine this, the vacuum pump characteristics must be determined for the MDP. This report details pump characteristics using an MDP backed by a Metal Bellows (Met-Bel) pump under static and flow conditions for various gases.

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Failure Formulations in Modular Plasticity Models

Computational prediction of ductile failure remains a challenging and important problem as demonstrated by the recent Sandia Fracture Challenges. In addition to emphasizing the complexity of such problems, the variety of solution strategies also highlighted the number of possible approaches to this problem. A common engineering approach for such efforts is to use a failure model in conjunction with element deletion. In the second Sandia Fracture Challenge, for instance, nine of the fourteen teams used some form of element deletion. For such schemes, a critical decision pertains to the selection of the appropriate failure model; of which many may be found in the literature (see the review of Corona and Reedlunn). The variety may also be observed in the aforementioned second Sandia Fracture Challenge in which at least eight different failure criteria are listed for the nine element deletion based approaches. The selection of the appropriate failure model is a difficult challenge depending on the material being considered and such criteria can variously depend on stress state (i.e. triaxiality, Lode angle) and loading conditions (i.e. strain rate, temperature). Separate implementations of each criteria with different plasticity models can be a repetitive and cumbersome process which may limit available models for an engineering analyst. To mitigate this issue, an effort was pursued to flexibly implement failure models in which different failure models could be specified and utilized within the same elastic-plastic constitutive routine by simply changing the input syntax. Similarly, the same models are implemented across a suite of elastic-plastic formulations enabling consistent definitions. As will be discussed later, a specific "modular failure" model is also implemented which allows for the selection or specification of different dependencies depending on the current need. At this stage, this effort is limited to defining failure models; progression/damage evolution in the constitutive model is not treated and left to future efforts.

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Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Ultrasonic transmission is sensitive to the spatial variation in mechanical properties of materials due to the presence of cracks/fractures. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-informed unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing. Novelty of the work involves the assignment of both statistically consistent and physically consistent clusters to the measurements of shear waveforms acquired across the one axial and two frontal planes. Physically consistent/relevant information is incorporated by considering the travel time of the peak of spectral energy and transmission coefficient of the transmitted waveform. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. Finally, the proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

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