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At least 685 records · Page 38

Large Scale Bilevel Optimization for N-K SCOPF Using Adversarial Robustness

Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over k simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach. We develop new efficient methods to solve each level of the bilevel optimization by employing knowledge of the physics of the underlying system. This yields significant improvements in speed and convergence that enable us to address the N-k SCOPF problem at scale. We demonstrate the effectiveness of our method by conducting a comprehensive analysis of an N-3 SCOPF for a 500-bus network. Furthermore, we emphasize the ability of our physics-driven techniques to handle larger systems by successfully scaling up to 12,000 buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reducing model error using optimized galaxy selection: weak lensing cluster mass estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density Σ crit relative modelling bias on the 60-70% level, while maintaining up to 90% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Systems and methods for fast detection of elephant flows in network traffic

In a system for efficiently detecting large/elephant flows in a network, the rate at which the received packets are sampled is adjusted according to a top flow detection likelihood computed for a cache of flows identified in the arriving network traffic. After observing packets sampled from the network, Dirichlet-Categorical inference is employed to calculate a posterior distribution that captures uncertainty about the sizes of each flow, yielding a top flow detection likelihood. The posterior distribution is used to find the most likely subset of elephant flows. The technique rapidly converges to the optimal sampling rate at a speed O(1/n), where n is the number of packet samples received, and the only hyperparameter required is the targeted detection likelihood.

Gudibanda, Aditya↗

Three-energy focusing Laue monochromator for the diamond light source x-ray pair distribution function beamline I15-1

The I15-1 beamline, the new side station to I15 at the Diamond Light Source, will be dedicated to the collection of atomic pair distribution function data. A Laue monochromator will be used consisting of three silicon crystals diffracting X-rays at a common Bragg angle of 2.83°. The crystals use the (1 1 1), (2 2 0), and (3 1 1) planes to select 40, 65, and 76 keV X-rays, respectively, and will be bent meridionally to horizontally focus the selected X-rays onto the sample. All crystals will be cut to the same optimized asymmetry angle in order to eliminate image broadening from the crystal thickness. Finite element calculations show that the thermal distortion of the crystals will affect the image size and bandpass.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

End-hole Versus Microvalve Infusion Catheters in Patients Undergoing Drug-Eluting Microspheres-TACE for Solitary Hepatocellular Carcinoma Tumors: A Retrospective Analysis

Introduction: Pre-transplant locoregional therapy for hepatocellular carcinoma (HCC) during bridge-to-transplant impacts recurrence and survival rates following liver transplantation. Optimizing the effectiveness of transarterial chemoembolization (TACE) in this population is imperative, and microvalve infusion catheters offer a means of such improvement. Methods: All treatment-naive patients with solitary HCC tumors < 6.5 cm who underwent drug-eluting microspheres (DEM) TACE between 04/2015 and 08/2017 were retrospectively reviewed. Eighty-eight included patients underwent DEM-TACE with either standard end-hole catheters (EH) or microvalve infusion catheters (MVI). The EH (n = 70) and MVI (n = 18) cohorts had similar baseline tumor size, laboratory values, and tumor etiologies. Results: Initial objective response rates were significantly higher in MVI vs. EH (100% vs. 76.5%, p = 0.019). There was no difference in adverse events between groups (p = 0.265). MVI patients exhibited lower AST (p = 0.003) and ALT (p = 0.044) at 6 months. Blinded pathological analysis of explanted livers showed greater concentrations of microspheres within the tumor relative to the surrounding tissue in MVI explants (88.7 ± 10.6%) versus the EH explants (55.3 ± 32.7%) (p = 0.002). There was significantly higher percentage tumor necrosis in the MVI group (89.0 ± 2.2%) compared with the EH group (56.1 ± 44.5%) (p = 0.006). Conclusion: In this retrospective study of a single-center cohort, DEM-TACE procedures with MVI were associated with improved tumor response, increased deposition of microspheres within tumor tissue, and higher percentage tumor necrosis at explant relative to those performed using EH catheters.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Dopant site-dependent luminescence from rare-earth doped dibarium octafluorohafnate Ba 2 HfF 8 nanocubes for radiation detection

Development of new host materials containing heavy elements for radiation detection is highly desirable. In this work, dibarium octafluorohafnate, Ba 2 HfF 8 , doped with rare-earth ions, was synthesized as cube-shaped nanocrystals via a facile hydrothermal method. The host lattice contains two Ba 2+ crystallographic sites, and dopants on these sites exhibit site-dependent photoluminescence (PL), cathodoluminescence (CL) and X-ray excited radioluminescence (RL) characteristics. Single doping contents were optimized as 25 mol% Tb 3+ and 5 mol% Eu 3+ . In Ba 2 HfF 8 :Tb 3+ –Eu 3+ codoped nanocrystals, preferrable occupation of Eu 3+ and Tb 3+ at two different Ba 2+ sites in the host lattice was observed. The nanocubes exhibited enhanced emissions over micron sized particles. In PL, the presence of Tb3+ ions significantly enhanced the emission intensity of Eu 3+ ions due to energy transfer from the Tb 3+ to Eu 3+ ions, while under high-energy irradiation in CL or RL, Tb 3+ emission was intensified. X-ray induced RL with afterglow in seconds was observed. Finally, it was found that the codoped sample showed higher sensitivity than the singly doped sample, indicating that codoping is an effective strategy to develop a scintillator with this host structure for high-energy radiation detection.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Rapid synthesis of flower shaped Cu{sub 2}ZnSnS{sub 4} nanoparticles by microwave irradiation for solar cell application

Single phase Cu{sub 2}ZnSnS{sub 4} (CZTS) nanoparticles have been synthesized by the microwave-assisted solution method in a one step process. Structural, morphological and optical characterizations of the CZTS nanoparticles have been carried out. X-ray diffraction confirms the single phase formation of CZTS nanoparticles with kesterite structure. SEM confirms the homogenous distribution of CZTS nanoparticles flower like assemblies. High resolution TEM image confirms the good crystallinity of the CZTS nanoparticles with the average grain size ~20 nm. The CZTS nanoparticles have strong optical absorption in the visible region with direct band gap as ~1.6 eV which is optimal for photovoltaic application.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

Avatar Tools

Supervised machine learning is the process of using past experience to predict the future. "Ensembles" are a machine-learning meta-method that can be applied to most machine learning algorithms. Ensembles generally greatly improve accuracy, reduce or remove most of the design issues presented by machine learning, and are admirably suited to parallel and distributed computation. The Avatar Tools codes are an implementation of ensembles specifically for decision trees. Some features that distinguish Avatar Tools from other "ensembles for decision trees" codes are: (1) Does the bookkeeping necessary for out of bag (OOB) validation. (2) Can use OOB validation to automatically determine optimal ensemble size. (3) Provides an MPI-based parallel implementation, for distributed operation. (4) Provides convenient tools for cross-validation, to assess the accuracy provided by a training set. SAND2020-3858 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Siefert, Christopher↗

Potential Energy, Demand, Emissions, and Cost Savings Distributions for Buildings in a Utility’s Service Area

Several companies, universities, and national laboratories are developing urban-scale energy modeling that allows the creation of a digital twin of buildings for the simulation and optimization of real-world, city-sized areas. Prior to simulation-based assessment, a baseline of savings for a set of utility-defined use cases was established to clarify the initial business case for specific energy efficient building technologies. In partnership with a municipal utility, 178,337 OpenStudio and EnergyPlus models of buildings in the utility’s 1400 km 2 service area were created, simulated, and assessed with measures for quantifying energy, demand, cost, and emissions reductions of each building. The method of construction and assumptions behind these models is discussed, definitions of example measures are provided, and distribution of savings across the building stock is provided under a maximum technical adoption scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multicompartment Polymeric Nanoreactors for Non-Orthogonal Cascade Catalysis

Spatial confinement of multiple catalysts presents an effective strategy for performing sequential or tandem chemical transformations in a one-pot reaction. These methods may be used to catalyze numerous reactions in conditions that are otherwise incompatible between catalyst and solvent, different catalysts, or reagents. Appropriate site isolation or support structure design would lead to significant advantages in atom economy, purification, and costs and the development of the interface between a catalyst and its confined microenvironment is paramount for realizing the next-generation of nanoreactors. Polymer scaffolds can create tailor-made microenvironments resulting in catalyst compartmentalization. Through the optimization of a number of variables such as size, solubility, functionality, and morphology of the nanoreactor, catalyst activity and selectivity can be tuned. In this Feature Article, we introduce design principles and early strategies for polymer supports for catalyst site-isolation and discuss current strategies towards multi-compartment polymer nanoreactors for non-orthogonal cascade catalysis. We conclude by outlining future design trends in this burgeoning field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Carbon Ferrochrome Effects on Microstructure and Mechanical Properties of Powder Metallurgy Titanium Alloys

In this paper, the powder metallurgy method was employed to prepare titanium alloys with high-carbon ferrochrome (HCFeCr). With the HCFeCr addition, the size of the β grains decreased and the lamellae of the α phase became thinner. The TiC strengthening phase precipitated at the grain boundaries, resulting in the inhibition of the β grain growth and hardness enhancement. In addition, Fe and Cr as β-stabilizing elements existed in the enriched β-Ti phase, which increased the β phase amount. The strength improvement was attributed to grain size optimization and strengthening phase formation. With the 9 wt.% HCFeCr addition, the corresponding Vickers hardness increased to 480 HV, which is 60% higher than the Ti6Al4V alloy. The tensile and yield strength was 1228 and 1140 MPa, respectively. The addition of HCFeCr can effectively enhance the strength and hardness while reducing the cost. This is a promising additive to obtain low-cost Ti alloys with high mechanical properties.

36 MATERIALS SCIENCE↗

Irradiation route to aqueous synthesis of highly luminescent ZnSe quantum dots and its function as a copper ion fluorescence sensor

Highlights: • Radiation chemical technique can provide a useful route for synthesis of ZnSe QDs. • Chelating nature of ethylene diamine is exploited for capping nanoparticles. • ZnSe QDs can be a suitable sensitive alternative to toxic cadmium-based system. • Cu(II) ion is probed by QDs in the presence of other physiologically relevant ions. - Abstract: Size-controlled synthesis of stable ZnSe QDs with narrow distribution in aqueous environment through conventional soft chemical method still poses a challenge. The proposed radiation assisted strategy demonstrates aqueous synthesis of stable, monodisperse and luminescent ZnSe QDs capped with chelating ethylene diamine under ambient conditions and at room temperature. Radiation chemical method facilitates in slow and in-situ release of selenium ion from sodium selenosulfate. The concentrations of precursors, such as zinc salt, selenium source, ethylene diamine and absorbed radiation (7–90 kGy) dose were optimized for obtaining good quality particles. Selective quenching of luminescence of as-synthesized quantum dots (QDs) by Cu{sup 2+} ions vis-à-vis other physiologically important cations provide evidence for use of ZnSe quantum dots as alternative to toxic Cd-based quantum dots to probe Cu{sup 2+} ions. The linear relation of ratio of loss in emission intensity as a function of concentration of Cu(II) indicates detection limit in nano-molar range.

36 MATERIALS SCIENCE↗

A graphics processing unit accelerated sparse direct solver and preconditioner with block low rank compression

We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU factorization which makes use of compression methods to accelerate time to solution and reduce memory usage. Multiple compression schemes based on rank-structured and hierarchical matrix approximations are supported, including hierarchically semi-separable, hierarchically off-diagonal butterfly, and block low rank. Here, in this paper, we present the GPU implementation of the block low rank (BLR) compression method within a multifrontal solver. Our GPU implementation relies on highly optimized vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs, rocBLAS and rocSOLVER for AMD GPUs and the Intel oneAPI Math Kernel Library (oneMKL) for Intel GPUs. Additionally, we rely on external open source libraries such as SLATE (Software for Linear Algebra Targeting Exascale), MAGMA (Matrix Algebra on GPU and Multi-core Architectures), and KBLAS (KAUST BLAS). SLATE is used as a GPU-capable ScaLAPACK replacement. From MAGMA we use variable sized batched dense linear algebra operations such as GEMM, TRSM and LU with partial pivoting. KBLAS provides efficient (batched) low rank matrix compression for NVIDIA GPUs using an adaptive randomized sampling scheme. The resulting sparse solver and preconditioner runs on NVIDIA, AMD and Intel GPUs. Interfaces are available from PETSc, Trilinos and MFEM, or the solver can be used directly in user code. We report results for a range of benchmark applications, using the Perlmutter system from NERSC, Frontier from ORNL, and Aurora from ALCF. For a high frequency wave equation on a regular mesh, using 32 Perlmutter compute nodes, the factorization phase of the exact GPU solver is about 6.5× faster compared to the CPU-only solver. The BLR-enabled GPU solver is about 13.8× faster than the CPU exact solver. For a collection of SuiteSparse matrices, the STRUMPACK exact factorization on a single GPU is on average 1.9× faster than NVIDIA’s cuDSS solver.

97 MATHEMATICS AND COMPUTING↗

Advanced manufacturing of 3D custom boron-carbide collimators designed for complex environments for neutron scattering

Scattered-beam collimation is a very useful method to reduce unwanted backgrounds and to boost the desired sample signal instead. This approach is of particular interest for samples contained within a complex environment that gives rise to much unwanted parasitic scatter. As neutron scattering instrument and techniques advances, small samples are becoming of more and more interest, which necessitates optimized collimation. Here, in this work, we describe a concept for the design and fabrication of advanced scattered-beam collimation 3D printed from B 4 C specifically tailored for samples contained within a complex environment. This concept is demonstrated through the use of a diamond anvil cell for high pressure experimentation, a technique that very typically requires small samples. The collimators here are designed through a modeling procedure via Monte Carlo neutron ray tracing that encompasses the entire system: the instrument, the complex environment and the collimator. Since the first approach of simply scaling up of the print-size was not successful, a novel concept of a multi-part alternate-blade collimator was developed. This approach addresses printing constraints but gives greater flexibility in design. Its performance is computationally compared against an unprintable progressively tighter blade collimator to assess the effect of alternating blades. No strong difference was observed. Its performance was validated through experimentation at the Spallation Neutron Source. The results emphasize the critical importance of ultra-high precision alignment while showing good overall agreement between simulation and experiment and underscore the feasibility of the method and its real-world application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Green Design of a Cellulosic Butanol Supply Chain Network: A Case Study of Sorghum Stem Bio-butanol in Missouri

Cellulosic butanol is a very promising renewable fuel to consider for the future transportation market. However, the seasonal availability of the raw materials, high maintenance cost, and high logistical cost of the biomass energy supply chain are the main factors impeding the commercialization and large-scale-production of this energy source. Furthermore, research focusing on an environmental or green supply chain network design of cellulosic butanol has been insufficient. Here, this study focused on designing a green supply chain network for cellulosic butanol. A life cycle analysis was integrated into a multi-objective linear programming model to optimize the cellulosic butanol supply chain network. With the objectives of maximizing the economic profits and minimizing the greenhouse gas emissions, the proposed model can optimize the location and size of a bio-butanol production plant. The mathematical model was applied to a case study in the state of Missouri, and solved the tradeoff between the feedstock and market availabilities of sorghum stem bio-butanol.

09 BIOMASS FUELS↗

Printable Fiber Reinforced Cement Composites – Feasibility Study

Additive manufacturing is enabling the manufacturability of structures with previously unattainable complexity or functionality, and there is growing interest in additive manufacturing of “printed” concrete structures. The focus of this Phase 1 Technical Collaboration (TC) project was to evaluate feasibility of printing hybrid cement composite structures reinforced with textile carbon fibers (tCF). This project leverages other (non-IACMI) projects on cement formulation and printing process development, as well as on the production process for tCF. This project’s primary focus was to explore cement composite mix design with textile carbon fibers to be manufactured by MonteFibre (TC partner) and evaluate suitable fiber-matrix interface or sizing for cement composites working with Michelman (TC Partner). This project supports IACMI’s goal of reducing the cost and embodied energy of carbon fiber composites. Cost is one of the fundamental challenges to carbon fiber reinforced cement composites. Cement is an extremely inexpensive material (approximately $\$$0.05/lb). Adding 1 wt% of conventional carbon fiber to cement quadruples its cost. Therefore, the need to use low-cost carbon fiber and ensure that the additional cost of the carbon fiber has a greater cost benefit to the final product. This was the first preliminary evaluation to integrate tCF reinforcement in cement composites, and such potential tCF utilization should significantly reduce materials cost. Cement composite production is energy and emissions intensive, thus by strengthening it less material will be required. Hence, the embodied energy and production time of the resulting structures will be reduced. Additionally, integrating these new materials into additive processes can enable selective use of the material in high load or stress areas. It is noteworthy that past work in this field of fiber reinforced cement composites did not consider the optimization of fiber-matrix interface using suitable sizing. Carbon fiber reinforcement offers potential added benefits of thermal conductivity (which affects cure rate) and flow behavior that could provide opportunities for site specific utilization of carbon fiber on hybrid cement structures (e.g. use the fiber reinforcement on outer surfaces to enhance strength and modulus and then infiltrating the internal structures with conventional concrete). MonteFibre was the industry lead and planned on supplying the tCF for this project. However, during the short Phase-1 duration of this project, MonteFibre was unable to produce tCF for this project due to manufacturing plant being off-line throughout the course of the project. The project team decided to pursue an alternate option which involved demonstrating printable concrete with steel fibers by the ORNL lead, Dr. Brian Post. The University of Tennessee collaboration team focused on evaluating the suitable chemical sizing for carbon fibers working with Michelman and also developed methods for material characterization of cement-based composites to evaluate the material response for compression, shear, flexure, and tension. The two milestones for University of Tennessee, Knoxville were realized related to identification of one sizing suitable for carbon fiber reinforced cement composite and developing data associated with mechanical behavior of unreinforced (neat) and carbon fiber reinforced cement composites. ORNL could not complete the task of carbon fiber reinforced printed cement composites due to the reasons mentioned earlier, but was able to replace tCF with steel fibers to demonstrate the feasibility of printing with fiber reinforced cement composites. The Project team reviewed possible sizing chemistry available in collaboration with Michelman for use on carbon fiber reinforcement in cement composites and concrete applications. Our initial goal was to identify a sizing most promising for formulation with textile carbon fibers (tCF) to deliver excellent mechanical properties in composite material state. Since tCF was not available for this project as originally envisioned, the team continued this task to identify a suitable sizing for carbon fiber applications by applying such sizing to lower cost carbon fibers currently available commercially from Zoltek called Panex fibers. At a future time this can be optimized for textile carbon fibers from Montefibre. The bulk of previous work on carbon fiber reinforced cement has neglected the importance of fiber-matrix adhesion on mechanical properties of the cement composite and identifying this missing link was an important accomplishment for future research. Tensile behavior of fiber reinforced concrete is important to evaluate in order to realize the dream of concrete products that do not need reinforcing steel. Important sample preparation and testing procedures were addressed in this study and it was concluded that substantial improvements in tensile behavior, without compromising compressive strength, and improved ductility can result from the use of carbon fiber reinforcement.

36 MATERIALS SCIENCE↗