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DOE OSTI2023

GUI Control System for the Mu2e Electrostatic Septum High Voltage at Fermilab

The Mu2e Experiment has stringent beam structure requirements; namely, its proton bunches with a time structure of 1.7 $\mu$s in the Fermilab Delivery Ring. This beam structure will be delivered using the Fermilab 8-GeV Booster, the 8-GeV Recycler Ring, and the Delivery Ring. The 1.7-$\mu$s period of the Delivery Ring will generate the required beam structure by means of a third order resonant extraction system operating on a single circulating bunch. The electrostatic septum (ESS) for this system is particularly challenging, requiring mechanical precision in a ultra high vacuum of 1 x 10$^-8$ Torr to generate 100 kV across 15 mm. This paper describes a graphical user interface that has been developed to automate the conditioning and commissioning process for the electrostatic septa. It is based on an interface to the Fermilab ACNET system using the ACSys Python Data Pool Manager (DPM) Client produced and maintained by Fermilab Accelerator Controls. Network interfacing between data pool managers made by the application and ACNET devices introduce an inherent (approximately 1 s) latency in throughput of the readouts. This delay is utilized to process and graph incoming data events of devices crucial to conditioning of a electrostatic septum (ESS). 'Ramping' and 'Monitoring' modes adjust settings of the power supply based on internal logic to efficaciously increase and maintain the high voltage (HV) in the ESS, easing the voltage setting on incidence of sparking or other possibly damaging events. A timestamped log file is produced as the application runs.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗

DOE OSTI2016

Selectively catalytic activity of metal–organic frameworks depending on the N-position within the pyridine ring of their building blocks

Iron metal–organic frameworks (MOFs) [Fe(L){sub 2}(SCN){sub 2}]{sub ∝} (L1: 4-bpdh=2,5-bis(4-pyridyl)-3,4-diaza-2,4-hexadiene for 1Fe; and L2: 3-bpdh=2,5-bis(3-pyridyl)-3,4-diaza-2,4-hexadiene for 2Fe) were assembled in a MeOH–H{sub 2}O solvent system. 1Fe exhibits a two-dimensional extended-grid network, whereas 2Fe exhibits a stair-like double-chain; the N-position within the pyridine ring of the complexes was observed to regulate the MOF structure as layers or chains. Furthermore, selectively catalytic activity was observed for the layered MOF but not the chain-structured MOF; micro/nanoparticles of the layered MOF were therefore investigated for new potential applications of micro/nano MOFs. - Graphical abstract: Iron metal–organic frameworks (MOFs) [Fe(L){sub 2}(SCN){sub 2}]{sub ∝} (L1: 4-bpdh=2,5-bis(4-pyridyl)-3,4-diaza-2,4-hexadiene for 1Fe; and L2: 3-bpdh=2,5-bis(3-pyridyl)-3,4-diaza-2,4-hexadiene for 2Fe) were assembled in a MeOH–H{sub 2}O solvent system. The N-position within the pyridine ring of the complexes was observed to regulate the MOF structure as layers or chains. Selectively catalytic activity was observed for the layered MOF but not the chain-structured MOF. - Highlights: • Synthesis and structure of metal–organic framework [Fe(L){sub 2}(SCN){sub 2}]{sub ∝}. • Selectively catalytic activity depending on the N-position within the pyridine ring. • The degradation and conversion of methyl orange.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Bringing Control System User Interfaces to the Web

With the evolution of web based technologies, especially HTML5 [1], it becomes possible to create web-based control system user interfaces (UI) that are cross-browser and cross-device compatible. This article describes two technologies that facilitate this goal. The first one is the WebOPI [2], which can seamlessly display CSS BOY [3] Operator Interfaces (OPI) in web browsers without modification to the original OPI file. The WebOPI leverages the powerful graphical editing capabilities of BOY and provides the convenience of re-using existing OPI files. On the other hand, it uses generic JavaScript and a generic communication mechanism between the web browser and web server. It is not optimized for a control system, which results in unnecessary network traffic and resource usage. Our second technology is the WebSocket-based Process Data Access (WebPDA) [4]. It is a protocol that provides efficient control system data communication using WebSocket [5], so that users can create web-based control system UIs using standard web page technologies such as HTML, CSS and JavaScript. WebPDA is control system independent, potentially supporting any type of control system.

Chen, Xihui↗

DOE OSTI2014

Crystal structure and orbital-singlet state of Ag{sub x}VP{sub 2}O{sub 7}

The crystal structure and electronic properties of Ag{sub x}VP{sub 2}O{sub 7} with a wide composition range of 0.7≤x≤1 synthesized newly are explored through measurements of X-ray four-circle diffraction, electrical resistivity, and magnetization. This system is monoclinic with space group P2{sub 1}/c and the lattice constants for x=1 are a=7.3358(3) Å, b=8.0235(3) Å, c=9.5782(5) Å, β=111.940(4)°, and V=522.93(5) Å{sup 3}. The structure is described in terms of VO{sub 6} octahedra which are bridged with P{sub 2}O{sub 7} groups to form a three-dimensional network with the hexagonal tunnels that a pair of Ag ions apparently resides in. The crystal field of V ions is intermediate and the electron configuration has the orbital-singlet ground state with a gap of the order of 10 K to the doublet state. - Graphical abstract: (a) The temperature dependencies of inverse magnetic susceptibilities for Ag{sub x}VP{sub 2}O{sub 7} with x=0.7−1 and (b) the low-temperature susceptibilities. - Highlights: • Ag{sub x}VP{sub 2}O{sub 7} system with 0.7<x<1 is prepared. • The crystal structure and electronic properties are clarified. • The electron configuration has the orbital-singlet ground state. • The electron hopping and the V–O covalency are reduced significantly. • The Ag deficiency gives rise to the charge separation of V{sup 3+} and V{sup 5+}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Langston University - High Energy Physics (LU-HEP)

This final report is presented by Langston University (LU) for the project entitled "Langston University High Energy Physics" (LUHEP) under the direction of principal investigator (PI) and project director Professor Joel Snow. The project encompassed high energy physics research performed at hadron colliders. The PI is a collaborator on the DZero experiment at Fermi National Accelerator Laboratory in Batavia, IL, USA and the ATLAS experiment at CERN in Geneva, Switzerland and was during the entire project period from April 1, 1999 until May 14, 2012. Both experiments seek to understand the fundamental constituents of the physical universe and the forces that govern their interactions. In 1999 as member of the Online Systems group for Run 2 the PI developed a cross-platform Python-based, Graphical User Interface (GUI) application for monitoring and control of EPICS based devices for control room use. This served as a model for other developers to enhance and build on for further monitoring and control tasks written in Python. Subsequently the PI created and developed a cross-platform C++ GUI utilizing a networked client-server paradigm and based on ROOT, the object oriented analysis framework from CERN. The GUI served as a user interface to the Examine tasks running in the D\O\ control room which monitored the status and integrity of data taking for Run 2. The PI developed the histogram server/control interface to the GUI client for the EXAMINE processes. The histogram server was built from the ROOT framework and was integrated into the D\O\ framework used for online monitoring programs and offline analysis. The PI developed the first implementation of displaying histograms dynamically generated by ROOT in a Web Browser. The PI's work resulted in several talks and papers at international conferences and workshops. The PI established computing software infrastructure at LU and U. Oklahoma (OU) to do analysis of DZero production data and produce simulation data for the experiment. Eventually this included the FNAL SAM data grid system, the SAMGrid (SG) infrastructure, and the Open Science Grid software stacks for computing and storage elements. At the end of 2003 Snow took on the role of global Monte Carlo production coordinator for the DØ experiment. A role which continues til this day. In January of 2004 Snow started working with the SAMGrid development team to help debug, deploy, and integrate SAMGrid with DØ Monte Carlo production. Snow installed and configured SG execution and client sites at LUHEP and OUHEP, and a SG scheduler site at LUHEP. The PI developed a python based GUI (DAJ) that acts as a front end for job submission to SAMGrid. The GUI interfaces to the DZero Mone Carlo (MC) request system that uses SAM to manage MC requests by the physics analysis groups. DAJ significantly simplified SG job submission and was deployed in DZero in an effort to increase the user base of SG. The following year was the advent of SAMGrid job submission to the Open Science Grid (OSG) and LHC Computing Grid (LCG) through a forwarding mechanism. The PI oversaw the integration of these grids into the existing production infrastructure. The PI developed an automatic MC (Automc) request processing system capable of operating without user intervention (other than getting grid credentials), and able to submit to any number of sites on various grids. The system manages production at all but 2 sites. The system was deployed at Fermilab and remains operating there today. The PI's work in distributed computing resulted in several talks at international conferences. UTA, OU, and LU were chosen as the collaborating institutions that form the Southwest Tier 2 Center (SWT2) for ATLAS. During the project period the PI contributed to the online and offline software infrastructure through his work with the Run 2 online group, and played a major role in Monte Carlo production for DZero. During the part of the project period in which the PI served as MC production coordinator MC production increased very significantly. In the first year of the PI's tenure as production coordinator production was 159M events and 6.7~TB of data. During the last year of the project period production was 2,342~M events and 262~TB of data. That is a factor of 15 increase in events and 39 in data volume. The increase occurred with improvements in computer hardware and networks, through the use of grid technology on diverse resources, and through increased automation and efficiency of the production process. LU HEP developed and deployed the automatic MC request processing system in use at FNAL. The complementary strategies of automation and grid production served DZero well. Fermilab has recognized LU HEP's contribution to DZero by allowing the PI to devote full time to research activities by appointing him a guest scientist for the last six years of the project period.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Machine Learning Tools Set for Natural Gas Fuel Cell System Design

This study is focusing on leveraging the system design tools set for the next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system. Conventionally, system design and optimization of NGFC systems rely heavily on traditional reduced order model (ROM) techniques and designers’ experience level. For overcoming the technical barriers of system design, multiple multi-physics models and machine learning (ML) tools have been utilized to automate the conceptual design process and enhance the reliability of solutions for the NGFC system. The proposed tools set includes a physics-informed ML tool for automated ROM construction that leverages advances in deep neural networks to significantly reduce ROM prediction error for the NGFC power island compared to traditional approaches. The constructed physics-informed ML ROM can be used in system design, and optimization tools set Institute for the Design of Advanced Energy Systems (IDAES) Process Systems Engineering (PSE) framework. The tools set also provides a user-friendly graphic user interface built within Jupyter Notebooks, and the complete tools set is open-source public available.

Wang, Dewei↗

DOE OSTI2022

GraphAlign: Graph-Enabled Machine Learning for Seismic Event Filtering

This report summarizes results from a 2 year effort to improve the current automated seismic event processing system by leveraging machine learning models that can operated over the inherent graph data structure of a seismic sensor network. Specifically, the GraphAlign project seeks to utilize prior information on which stations are more likely to detect signals originating from particular geographic regions to inform event filtering. To date, the GraphAlign team has developed a Graphical Neural Network (GNN) model to filter out false events generated by the Global Associator (GA) algorithm. The algorithm operates directly on waveform data that has been associated to an event by building a variable sized graph of station waveforms nodes with edge relations to an event location node. This builds off of previous work where random forest models were used to do the same task using hand crafted features. The GNN model performance was analyzed using an 8 week IMS/IDC dataset, and it was demonstrated that the GNN outperforms the random forest baseline. We provide additional error analysis of which events the GNN model performs well and poorly against concluded by future directions for improvements.

58 GEOSCIENCES↗

DOE OSTI2015

Using ASCEM modeling and visualization to inform stakeholders of contaminant plume evolution and remediation efficacy at F-Basin Savannah river, SC - 15156

Communication with stakeholders, regulatory agencies, and the public is an essential part of implementing different remediation and monitoring activities, and developing site closure strategies at contaminated sites. Modeling of contaminant plume evolution plays a critical role in estimating the benefit, cost, and risk of particular options. At the same time, effective visualization of monitoring data and modeling results are particularly important for conveying the significance of the results and observations. In this paper, we present the results of the Advanced Simulation Capability for Environmental Management (ASCEM) project, including the discussion of the capabilities of newly developed ASCEM software package, along the its application to the F-Area Seepage Basins located in the U.S. Department of Energy Savannah River Site (SRS). ASCEM software includes state-of-the-art numerical methods for simulating complex flow and reactive transport, as well as various tool-sets such as a graphical user interface (GUI), visualization, data management, uncertainty quantification, and parameter estimation. Using this software, we have developed an advanced visualization of tritium plume migration coupled with a data management system, and simulated a three-dimensional model of flow and plume evolution on a high-performance computing platform. We evaluated the effect of engineered flow barriers on a nonreactive tritium plume, through advanced plume visualization and modeling of tritium plume migration. In addition, we developed a geochemical reaction network to describe complex geochemical processes at the site, and evaluated the impact of coupled hydrological and geochemical heterogeneity. These results are expected to support SRS's monitoring activities and operational decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2013

Nb{sub 2}OsB{sub 2}, with a new twofold superstructure of the U{sub 3}Si{sub 2} type: Synthesis, crystal chemistry and chemical bonding

The new ternary metal-rich boride, Nb{sub 2}OsB{sub 2}, was synthesized by arc-melting the elements in a water-cooled copper crucible under an argon atmosphere. The compound was characterized from single-crystal X-ray data and EDX measurements. It crystallizes as a new superstructure (space group P4/mnc, no. 128) of the tetragonal U{sub 3}Si{sub 2}-structure type with lattice parameters a=5.922(1) Å and c=6.879(2) Å. All of the B atoms are involved in B{sub 2} dumbbells with B–B distances of 1.89(4) Å. Structure relaxation using VASP (Vienna ab intio Simulation Package) has confirmed the space group and the lattice parameters. According to electronic structure calculations (TB–LMTO–ASA), the homoatomic B–B interactions are optimized and very strong, but relatively strong heteroatomic Os–B, Nb–B and Nb–Os bonds are also found: These interactions, which together build a three-dimensional network, are mainly responsible for the structural stability of this new phase. The density of state at the Fermi level predicts metallic behavior, as expected, from this metal-rich boride. - Graphical abstract: Nb{sub 2}OsB{sub 2} is, to the best of our knowledge, the first fully characterized phase in the ternary Nb–Os–B system. It crystallizes (space group P4/mnc, 128) with a new twofold superstructure of the U{sub 3}Si{sub 2} structure type (space group P4/mbm, 127), and is therefore the first boride in this structure family crystallizing with a superstructure of the U{sub 3}Si{sub 2} structure type. We show that the distortions leading to this superstructure occurs mainly in the Nb-layer, which tries to accommodate the large osmium atoms. The consequence of this puckering is the building osmium dumbbells instead of chains along [001]. - Highlights: • First compound in the Nb–Os–B system. • New twofold superstructure of U{sub 3}Si{sub 2} structure type. • Puckering of Nb-layer responsible for superstructure occurrence. • Chemical bonding studied by density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Urban Deployment Model (UDM) v1.0

The software, called the Urban Deployment Model (UDM), is an integrated set of tools for the simulation and analysis of static and mobile radiation detection systems in complex urban environments. The UDM includes a graphical user interface through which the workflow associated with setting up and executing a simulation may be established. The modular toolsets combine aspects of radiation transport, navigation, graph theory, optimization, and visualization to allow the complete end-to-end simulation of large scale, highly-distributed sensor networks.

Abgrall, Nicolas↗

DOE OSTI2017

Software Comparison for Renewable Energy Deployment in a Distribution Network

The main objective of this report is to evaluate different software options for performing robust distributed generation (DG) power system modeling. The features and capabilities of four simulation tools, OpenDSS, GridLAB-D, CYMDIST, and PowerWorld Simulator, are compared to analyze their effectiveness in analyzing distribution networks with DG. OpenDSS and GridLAB-D, two open source software, have the capability to simulate networks with fluctuating data values. These packages allow the running of a simulation each time instant by iterating only the main script file. CYMDIST, a commercial software, allows for time-series simulation to study variations on network controls. PowerWorld Simulator, another commercial tool, has a batch mode simulation function through the 'Time Step Simulation' tool, which obtains solutions for a list of specified time points. PowerWorld Simulator is intended for analysis of transmission-level systems, while the other three are designed for distribution systems. CYMDIST and PowerWorld Simulator feature easy-to-use graphical user interfaces (GUIs). OpenDSS and GridLAB-D, on the other hand, are based on command-line programs, which increase the time necessary to become familiar with the software packages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Assessing electrogenetic activation via a network model of biological signal propagation

Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control. Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia. Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks. Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.

Chun, Kayla↗

DOE OSTI2016

Assembly of 4-, 6- and 8-connected Cd(II) pseudo-polymorphic coordination polymers: Synthesis, solvent-dependent structural variation and properties

The reaction of Cd(NO{sub 3}){sub 2}·4H{sub 2}O, 2,5-thiophenedicarboxylic acid (H{sub 2}tdc) and 1,2-bis(imidazol-1′-yl)methane (bimm) by modulating solvent systems yielded three highly connected pseudo-polymorphic coordination polymers based on different dinuclear [Cd{sub 2}(CO{sub 2}){sub 2}] subunits bridged by carboxylate groups. Single crystal structural analyses reveal structural variation from 4-connected 2D sql layer, 6-connected 2-fold interpenetrated 3D pcu to 8-connected 3D bcu-type network in compounds 1–3. The structural dissimilarity in the structures dependent on the coordination environments of Cd(II) ions and linking modes of mixed ligand influenced by different solvent systems during the synthesis process. Moreover, thermogravimetric and photoluminescence behaviors of 1–3 were also investigated for the first time, and all the complexes emit blue luminescence in the solid state. - Graphical abstract: Key Topic. Different solvent systems modulated three Cd(II) pseudo-polymorphic coordination polymers based on thiophene-2,5-dicarboxylate and 1,2-bis(imidazol-1′-yl)methane mixed ligands. Display Omitted - Highlights: • Three solvent-dependent Cd(II) pseudo-polymorphic coordination polymers have been synthesized. • Structural variation from 4-connected 2D layer, 6-connected 2-fold interpenetrated 3D net to 8-connected 3D net. • All complexes emit blue luminescence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗

DOE OSTI2022

A Review of Bayesian Networks for Spatial Data

We report Bayesian networks are a popular class of multivariate probabilistic models as they allow for the translation of prior beliefs about conditional dependencies between variables to be easily encoded into their model structure. Due to their widespread usage, they are often applied to spatial data for inferring properties of the systems under study and also generating predictions for how these systems may behave in the future. We review published research on methodologies for representing spatial data with Bayesian networks and also summarize the application areas for which Bayesian networks are employed in the modeling of spatial data. We find that a wide variety of perspectives are taken, including a GIS-centric focus on efficiently generating geospatial predictions, a statistical focus on rigorously constructing graphical models controlling for spatial correlation, as well as a range of problem-specific heuristics for mitigating the effects of spatial correlation and dependency arising in spatial data analysis. Special attention is also paid to potential future directions for integration of Bayesian networks with spatial processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

New vanadium tellurites: Syntheses, structures, optical properties of noncentrosymmetric VTeO{sub 4}(OH), centrosymmetric Ba{sub 2}V{sub 4}O{sub 8}(Te{sub 3}O{sub 10})

Two new vanadium tellurites, VTeO{sub 4}(OH) (1) and Ba{sub 2}V{sub 4}O{sub 8}(Te{sub 3}O{sub 10}) (2), have been synthesized successfully with the use of hydrothermal reactions. The crystal structures of the two compounds were determined by single-crystal X-ray diffraction. Compound 1 crystallizes in the polar space group Pca2{sub 1} (No. 29) while compound 2 crystallizes in the centrosymmetric space group C2/c (No. 15). The topography of compound 1 reveals a two-dimensional, layered structure comprised of VO{sub 6} octahedral chains and TeO{sub 3}(OH) zig-zag chains. Compound 2, on the contrary, features a three-dimensional [V{sub 4}O{sub 8}(Te{sub 3}O{sub 10})]{sup 4-} anionic framework with Ba{sup 2+} ions filled into the 10-member ring helical tunnels. The [V{sub 4}O{sub 8}(Te{sub 3}O{sub 10})]{sup 4-} anionic network is the first 3D vanadium tellurite framework to be discovered in the alkaline-earth vanadium tellurite system. Powder second harmonic generation (SHG) measurements indicate that compound 1 shows a weak SHG response of about 0.3×KDP (KH{sub 2}PO{sub 4}) under 1064 nm laser radiation. Infrared spectroscopy, elemental analysis, thermal analysis, and dipole moment calculations have also been carried out. - Graphical abstract: VTeO{sub 4}(OH) (1) crystallizes in the noncentrosymmetric space group Pca2{sub 1} (No. 29) while Ba{sub 2}V{sub 4}O{sub 8}(Te{sub 3}O{sub 10}) (2) crystallizes in the centrosymmetric space group C2/c (No. 15). - Highlights: • VTeO{sub 4}(OH) (1) and Ba{sub 2}V{sub 4}O{sub 8}(Te{sub 3}O{sub 10}) (2) have been synthesized successfully with the use of hydrothermal reactions. • VTeO{sub 4}(OH) (1) crystallizes in the noncentrosymmetric space group Pca2{sub 1} and displays a weak SHG response. • VTeO{sub 4}(OH) (1) represents only the fourth SHG-active material found in vanadium tellurite systems. • Ba{sub 2}V{sub 4}O{sub 8}(Te{sub 3}O{sub 10}) (2) exhibits a novel three-dimensional [V{sub 4}O{sub 8}(Te{sub 3}O{sub 10})]{sup 4-} anionic framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Target tracking via recursive Bayesian state estimation in cognitive radar networks

To cope with complicated environments and stealthier targets, incorporating intelligence and cognition cycles into target tracking is of great importance in modern sensor network management. With remarkable advances in sensor techniques and deployable platforms, a sensing system has freedom to select a subset of available radars, plan their trajectories, and transmit designed waveforms. In this paper, we propose a general framework for single target tracking in cognitive networks of radars, including consideration of waveform design, path planning, and radar selection, which are separately but not jointly taken into account in existing work. The tracking procedure, built on the theories of dynamic graphical models (DGM) and recursive Bayesian state estimation (RBSE), is formulated as two iterative steps: (i) solving a combinatorial optimization problem to select the optimal subset of radars, waveforms, and locations for the next tracking instant, and (ii) acquiring the recursive Bayesian state estimation to accurately track the target. Further, an illustrative example introduces a specific scenario in 2-D space. Simulation results based on the scenario demonstrate that the proposed framework can accurately track the target under the management of the network of radars.

47 OTHER INSTRUMENTATION↗