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SpaceWire model development technology for satellite architecture.

Packet switched data communications networks that use distributed processing architectures have the potential to simplify the design and development of new, increasingly more sophisticated satellite payloads. In addition, the use of reconfigurable logic may reduce the amount of redundant hardware required in space-based applications without sacrificing reliability. These concepts were studied using software modeling and simulation, and the results are presented in this report. Models of the commercially available, packet switched data interconnect SpaceWire protocol were developed and used to create network simulations of data networks containing reconfigurable logic with traffic flows for timing system distribution.

33 ADVANCED PROPULSION SYSTEMS↗

Strip2CubeFace user%3CU%2B2019%3Es manual.

Commercial Off The Shelf (COTS) software for producing linked virtual tours based on 360 degree panoramas are becoming more and more available. However, the best current products for taking the images, stitching them into 360 degree panoramas, and then linking them together into complex virtual tours require different and incompatible input and output formats. This program is designed to bridge the gap between the iPix Interactive Studio export format, which consists of a single JPEG with the six faces of a cube connected horizontally, with the six individual JPEGs needed to be imported into Panotour Pro software. This report describes how to use the software program Strip2CubeFace, which takes the cube-strip JPEG exported from iPix Studio and coverts it into six JPEGs representing the six cube faces that Panotour Pro imports. As such, it represents a necessary link between the two COTS software programs key to making virtual tours quickly and easily. It becomes one member of the suite of software programs known as %E2%80%9CRaPP-TOURS%E2%80%9D or Rapid Processing of PanoTours Software necessary to simulate managed access and other permission requesting arms control-type training exercises.

Forden, Geoffrey Ethan↗

A Computational-Experimental Study of Plasma Processing of Carbides at High Temperatures

The effects of plasma on carbides were computationally investigated for the ultimate development of adherent, dense scales such as Al 2 O 3 -TiO 2 systems toward oxidation resistance at 1873 K. An alumina scale forms on the carbide because of the significant stability of Al 2 O 3 as the outer scale adjacent to the gas phase compared to rutile, though TiO and Ti 2 O 3 may form as components of an inner layer of a complicated scale. A sequence of surface reactions starting with the adsorption of oxygen on the surface was applied to experimental data from Donnelly’s research group who reported the adsorption of O 2 in a plasma atmosphere as a function of power. In addition to the adsorbed oxygen (Oad) as the rate determining step, it controlled the cascading reaction sequence of the adsorbed species of AlO, AlO 2 and AlO 3 , as indicated in the present study. The rate of oxygen adsorption also depends on the ratio of the final to initial adsorbed oxygen as a function the oxygen potential. In a secondary research thrust, Ti 3 AlC was synthesized and subsequently oxidized. A 39Ti-14Al-47TiC (in wt%) mixture was equilibrated by using a pseudo-isopiestic technique to form ultimately an aggregate of Ti3AlC, Ti 2 AlC and TiC phases. The aggregate was primarily composed of Ti 3 AlC with minor amounts of Ti 2 AlC and TiC, as determined by an X-ray diffraction analysis. The Ti 3 AlC/Ti 2 AlC/TiC aggregate was subsequently oxidized at 1873 K to form a scale composed of an outer layer of Al 2 O 3 -TiO 2 -Al 2 TiO 5 with an inner layer consisting of TiO-Al 2 O 3 - Al 4 CO 3 . The measured scale thickness grew according to Wagner’s parabolic growth rate, which estimates an effective diffusion coefficient of 6 (10)-8 cm 2 /s. The scale appears to grow with Ti ions migrating outward from the Ti 3 AlC/Ti 2 AlC/TiC core and oxygen ions diffusing inwardly toward the core. The transient temperature distribution of a cylindrical, carbide packed bed (i.e., B4C) was simulated with COMSOL software to determine the response of the bed to a sudden temperature spike exposed to the outer wall of the bed. The temperature distribution of B4C was similarly heated and compared with Hf and Zr metal. The thermal conductivity of Hf and Zr is higher than the B4C packed bed and hence they respond quicker than B4C. The packed bed still takes approximately 1200 s to plateau the temperature distribution between the cylinder surfaces to the centerline of the carbide packed bed of 5 cm diameter. Though the modeling of the distributions in the carbide packed bed gives an understanding of the transient heat response behavior driven by radiation, the effect of the plasma on the surface temperature of individual carbide particles needs further investigation to understand the plasma contribution to densification of a carbide packed bed.

36 MATERIALS SCIENCE↗

Material Protection, Accounting, and Control Technologies (MPACT) Advanced Integration Roadmap

The development of sustainable advanced nuclear fuel cycles is a long-term goal of the Office of Nuclear Energy’s (DOE-NE) Fuel Cycle Technologies program. The Material Protection, Accounting, and Control Technologies (MPACT) campaign is supporting research and development (R&D) of advanced instrumentation, analysis tools, and integration methodologies to meet this goal (Miller, 2015). This advanced R&D is intended to facilitate safeguards and security by design of fuel cycle facilities. The lab-scale demonstration of a virtual facility, distributed test bed, that connects the individual tools being developed at National Laboratories and university research establishments, is a key program milestone for 2020. These tools will consist of instrumentation and devices as well as computer software for modeling, simulation and integration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Material Protection, Accounting, and Control Technologies (MPACT) Advanced Integration Roadmap

The development of sustainable advanced nuclear fuel cycles is a long-term goal of the Office of Nuclear Energy’s (DOE-NE) Fuel Cycle Technologies program. The Material Protection, Accounting, and Control Technologies (MPACT) campaign is supporting research and development (R&D) of advanced instrumentation, analysis tools, and integration methodologies to meet this goal (Miller, 2015). This advanced R&D is intended to facilitate safeguards and security by design of fuel cycle facilities. The lab-scale demonstration of a virtual facility, distributed test bed, that connects the individual tools being developed at National Laboratories and university research establishments, is a key program milestone for 2020. These tools will consist of instrumentation and devices as well as computer software for modeling, simulation and integration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Final Technical Report: Mu2e at the City University of New York

This DOE grant award for was for the period June 1, 2013 to March 31, 2016. Popp was awarded an internship in the Visiting Faculty Program at FNAL in summer of 2015; consequently the unused portion of summer salary funds allowed us to apply for a no-cost extension with our remaining funds until March 31, 2017. That support furnished us with the means to carry out numerous successful projects for Mu2e for nearly four years. Up to now, the driving force to our work has been dictated primarily by the Mu2e Project cost and schedule needs. Our work has been under the purview of three of the Working Groups to which we belong: Target Station, Electron Tracker, and Stopping Target Monitor. We have carried out a mix of bench-top testing tasks locally, more elaborate work at Fermilab every summer, and extensive software development and simulation studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Return on Investment (ROI) Framework Case Study: CTH.

CTH is a Eulerian code developed at Sandia National Laboratories capable of modeling the hydrodynamic response of explosives, liquids, gases, and solids. The code solves complex multi-dimensional problems characterized by large deformations and strong shocks that are composed of various material configurations. CTH includes models for material strength, fracture, porosity, and high explosive detonation and initiation. The code is an acronym for a complex series of names relating to its origin. A full explanation can be seen in Appendix A. The software breaks penetration simulations into millions of grid-like “cells”. As a modeled projectile impacts and penetrates a target, progressively smaller blocks of cells are placed around the projectile, which show in detail deformations and breakups. Additionally, the code is uniquely suited to modeling blunt impact and blast loading leading to human body injury.

42 ENGINEERING↗

Material Protection, Accounting and Control Technologies (MPACT) Implementation Plan: Lab-Scale Demonstration of Advanced Safeguard and Security Systems

The Materials Protection, Accounting, and Control Technologies (MPACT) campaign is working towards the goal of developing and demonstrating the next generation of nuclear materials management for the peaceful use of civilian nuclear energy. A major milestone of the campaign is the “Lab-scale demonstration of an advanced safeguards and security system,” due in 2020. This implementation plan describes how tools developed in the MPACT campaign will be used to meet this milestone. These tools consist of instrumentation and devices as well as computer software for modelling, simulation and integration of data and information for safeguard and security analysis. The plan is focused on demonstrating an advanced safeguard and security systems for electrochemical processing plants, but also identifies activities needed to address advanced reactor, aqueous processing and other advanced fuel cycle facilities. A key component to achieving the 2020 milestone is the development of a virtual distributed test bed that incorporates the instruments, data, analysis tools, and models currently under development and provides a framework to link and normalize the data in a way that simulates a facility, including uncertainty quantification. This virtual distributed test bed will integrate computer simulated facilities that make up a fuel cycle of interest, with distributed test beds located in actual operating facilities and laboratories. The MPACT campaign recently issued roadmaps for both Modelling & Simulation and Advanced Integration which address this component, and activities necessary to achieve the 2020 milestone. Research, development and testing of specific technologies have been supported by the MPACT campaign in coordination with other DOE-NE and DOE-NNSA programs. These technologies provide the essential data needed by the safeguard and security systems, and feed into the data analysis and facility models. This plan will identify these technologies, their current status and activities needed to demonstrate the technologies at the laboratory scale. Wherever possible, test of technologies in field conditions using suitable nuclear materials will be used to define performance. Where necessary, surrogate materials and/or simulation will be used to provide useful information for the demonstration. When completed, the 2020 milestone will provide a demonstration of advanced safeguard and security technologies, including advanced modelling, simulation and analysis approaches, applied to electrochemical processing. It will also identify applications of the technology and approaches in other advanced fuel cycle and reactor concepts.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

sUAS Support for Mars 2020

The release of airborne radioactive material presents a health risk hazard to many individuals, including emergency responders and the public. Characterizing the unknown radioactive dangers produced during such incidents is essential. An advantage to utilizing unmanned aerial systems in this effort is the reduction of risk to personnel otherwise tasked with characterization, as well as more quickly obtaining data points during cloud immersion. By pairing a continuous air monitor (CAM) and detector with a drone, quantification of unknown material in the plume can be determined, and thus the extent of dose to people in the area can be estimated. A small, low-flow air sampler with a Geiger-Mueller counter may be characterized using experimental measurements of point sources representing a cloud of material and modelled using the Monte Carlo N-Particle Transport Code (MCNP), a software package for simulating nuclear processes, to find the usefulness and advantages of the system for detection of nuclides of concern in various nuclear plume scenarios. The flying time of small-unmanned aircraft systems (sUASs) is limited; thus, the minimum detectable activity and concentration rates possible must be determined over the system’s window of operation. While the activity concentrations corresponding to external and internal doses of concern can be detected with certainty for 90 Sr and 137 Cs in a plume, those corresponding to 238 Pu are more difficult to detect. The central principle of employing the sUAS is that the cockpit does not have an operator onboard the aircraft; therefore, control of the aircraft must take place by other means. With a sUAS, command and control can be separated into three distinct methods: (1) ground control or remote piloting, (2) semi-autonomous control, and (3) autonomous control. The isotope 238 Pu is used in the space industry, providing long-lived heat generation for fuel in outer space (NASA 2014). Due to the inherent risks with rocket launches to get objects into space, monitoring for release of these hazardous substances is a major undertaking. The current means is through employment of environmental CAMs. It is conceivable, however, that drone monitoring for release of 238 Pu in the event of a space launch mishap would give a greater chance of detection of plutonium particulate, because the particulate’s diffusion in air upon settling to the ground would make the probability of collecting a particle on a filter in a CAM very low.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Physics of the Serrano Sn Transport Package

Serrano is a software package for simulating photon transport in moving material. It presently supports 1-D, unstructured 2-D for a wide variety of element types, and 3-D for tetrahedra and hexahedra. The package is designed to be a component of larger codes, such as radiation hydrodynamics codes. Only the radiation transport equations are solved by Serrano itself.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

Chemical Reactivity Through Adaptive Quantum Mechanics/Many-Body Representations: Theoretical Development, Software Implementation, and Applications (Final Report)

The main objective of this research project was the development and application of a new theoretical/computational framework to model chemical transformations and electronic excitations in fluid mixtures across different phases. Our theoretical/computational framework combines our data-driven many-body (DD-MB) potentials representing molecular interactions with adaptive schemes for modeling chemical reactions in solution. The combination of these two components resulted in an adaptive quantum mechanics/many-body (adQM/MB) method that largely suppresses discontinuities between QM and MM regions, which affect existing QM/MM methods, and thus provides an accurate representation of both quantum mechanical and environmental effects through a rigorous description of mutual polarization between QM and MM regions. The implementation of our DD-MB potentials and adQM/MB method in popular software enabled computer simulations of solvation phenomena, reactive processes, and electronic excitations in fluid mixtures with chemical and spectroscopic accuracy, representing a major step toward realistic computer simulations of a wide range of molecular systems relevant to the DOE mission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing an Energy-Conscious Traffic Signal Control System for Optimized Fuel Consumption in Connected Vehicle Environments

The project titled “Developing an Energy-Conscious Traffic Signal Control System for Optimized Fuel Consumption in Connected Vehicle Environments” addresses energy-related challenges associated with adaptive traffic control systems by integrating connected vehicles (CV) and connected infrastructure (CI). The system developed in this project, a CV-based adaptive traffic control system, aims to improve fuel consumption in mixed traffic environments by capitalizing on emerging CV and CI communication technologies, as well as leveraging recent advances in Artificial Intelligence (AI), optimization, and edge computing. The system was tested at the MLK Smart Corridor, an urban testbed managed by the University of Tennessee at Chattanooga (UTC) and the City of Chattanooga. The system was validated through extensive simulations, both Software-in-the-Loop (SILS) and Hardware-in-the-Loop (HILS), and was further implemented and tested in real-world conditions at several intersections along the corridor. The Fuel Consumption Performance Index (FC-PI) and the Ecological Performance Index (Eco-PI) were developed as the key components for evaluating the system’s impact on fuel consumption and emissions. These metrics provided a comprehensive means of understanding the impact of traffic signal control optimization in mixed traffic environments. The report presents an in-depth analysis of the Eco-PI, FC-PI, adaptive traffic control system integration, and the testing and field implementation of the system. The results demonstrate significant reductions in fuel consumption and emissions, showcasing the system’s capability to contribute to more sustainable urban traffic management. The report also documents the challenges encountered and recommendations for scaling and further improving the system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NetMOD

NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The initial version of the software supports the simulation of seismic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria.

Merchant, Bion John↗

NetMOD v. 1.0

NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The version 2.0 of the software supports the simulation of seismic, hydroacoustic, and infrasonic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria. NetMOD will be distributed with a project file defining the basic performance characteristics of the International Monitoring System (IMS), a network of sensors operated by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Network modeling is needed to be able to assess and explain the potential effect of changes to the IMS, to prioritize station deployment and repair, and to assess the overall CTBTO monitoring capability currently and in the future. Currently the CTBTO uses version 1.0 of NetMOD, provided to them in early 2014. NetMOD will provide a modern tool that will cover all the simulations currently available and allow for the development of additional simulation capabilities of the IMS in the future. NetMOD simulates the performance of monitoring networks by estimating the relative amplitudes of the signal and noise measured at each of the stations within the network based upon known geophysical principles. From these signal and noise estimates, a probability of detection may be determined for each of the stations. The detection probabilities at each of the stations may then be combined to produce an estimate of the detection probability for the entire monitoring network.

Merchant, Bion J↗

Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm

The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.

D estefani, André↗

PyPWA: A Partial-Wave/Amplitude Analysis Software Framework

The PyPWA project aims to develop a software framework for Partial Wave and Amplitude Analysis of data; providing the user with software tools to identify resonances from multi-particle final states in photoproduction. Most of the code is written in Python. The software is divided into two main branches: one general-shell where amplitude's parameters (or any parametric model) are to be estimated from the data. This branch also includes software to produce simulated data-sets using the fitted amplitudes. A second branch contains a specific realization of the isobar model (with room to include Deck-type and other isobar model extensions) to perform PWA with an interface into the computer resources at Jefferson Lab. We are currently implementing parallelism and vectorization using the Intel's Xeon Phi family of coprocessors.

Salgado, Carlos↗