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At least 1,549 records · Page 86

A Data Exchange Interface for a Standards Based Data Integration Platform

The modern electrical grid is a complex and a data rich system, requiring several sub-systems to provide the capability and support needed to perform functions such as distributed energy resource management, outage management, and fault location and isolation, to name a few. There is a need to develop software solutions and platforms that provide an integrated infrastructure to allow interoperability between these subsystems, while leveraging the abundant data available from today’s grid. In this paper, we present the development and deployment of an application service to integrate GridAPPS-D which is an open source, standards-based software platform with SurvalentONE, a commonly used DNP3 based ADMS platform that allows operation, monitoring, analysis, restoration, and optimization of network operations. We present details of the integration architecture, including its implementation, and provide results from functional testing of the architecture on a 13 bus IEEE system. The results validate that the integration is successful and is able to provide a two-way exchange of communication and translation between different communication protocols.

Singh, Alka↗

Graph Sparsification by Approximate matrix Multiplication

Graphs arising in statistical problems, signal processing, large networks, combinatorial optimization, and data analysis are often dense, which causes both computational and storage bottlenecks. One way of sparsifying a weighted graph, while sharing the same vertices as the original graph but reducing the number of edges, is through spectral sparsification. We study this problem through the perspective of RandNLA. Specifically, we utilize randomized matrix multiplication to give a clean and simple analysis of how sampling according to edge weights gives a spectral approximation to graph Laplacians, without requiring spectral information. Through the CR–MM algorithm, we attain a simple and computationally efficient sparsifier whose resulting Laplacian estimate is unbiased and of minimum variance. Here, we define a new notion of additive spectral sparsifiers, which has not been considered in the literature.

97 MATHEMATICS AND COMPUTING↗

A Field Enhancement Integration Design Featuring Misalignment Tolerance for Wireless EV Charging Using LCL Topology

This article proposes a magnetic integration design for EV wireless power transfer (WPT) systems, where the compensation and transmitting coils overlap one on top of the other to share the ferrite layer without any decoupling consideration. The magnetic field generated by both the compensation and transmitting coils are exploited to transfer power. To this end, a compensation method is proposed to enable magnetic field enhancement without any reactive power flow between the compensation and the transmitting coils, and to achieve input zero phase angle and constant current output. In addition, an efficient finite element analysis-based coil optimization algorithm is proposed to improve the coil misalignment tolerance on the horizontal plane, in which a reversely connected inner coil is used to stabilize the system output under misalignment conditions. Analytical and simulation results confirm transmission flux density enhancement and reduced leakage field characteristics of the proposed coil design. Finally, a scaled-down WPT prototype is built and tested to verify the performance and effectiveness of the design. The proposed design achieves 91.17% efficiency and misalignment tolerance up to 200 mm in any XY-direction while maintaining the power transfer and its efficiency. The results of this work provide insights into magnetic integration design of high-order compensation topologies featuring higher compactness, less ferrite usage, magnetic field enhancement, and misalignment tolerance for WPT systems.

42 ENGINEERING↗

Bayesian optimized collection strategies for fatigue strength testing

Abstract A statistical framework is presented enabling optimal sampling and analysis of constant life fatigue data. Protocols using Bayesian maximum entropy sampling are built based on conventional staircase and stress step methods, reducing the requirement of prior knowledge for data collection. The Bayesian Staircase method shows improved parameter estimation efficiency, and the Bayesian Stress Step method shows equal accuracy to the standard method at larger step size allowing experimentalists to lessen concerns of loading history. Statistical methods for determining model suitability are shown, highlighting the influence of protocol. Experimental validation is performed, showing the applicability of the methods in laboratory testing.

36 MATERIALS SCIENCE↗

Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy

Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped; the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 Multiplication-Sign 376 Multiplication-Sign 630 voxels. Conclusions: The proposed needle segmentation algorithm is accurate, robust, and suitable for 3D TRUS guided prostate transperineal therapy.

60 APPLIED LIFE SCIENCES↗

Experimental investigation of performance differences between coherent Ising machines and a quantum annealer

Physical annealing systems provide heuristic approaches to solving combinatorial optimization problems. Here, we benchmark two types of annealing machines—a quantum annealer built by D-Wave Systems and measurement-feedback coherent Ising machines (CIMs) based on optical parametric oscillators—on two problem classes, the Sherrington-Kirkpatrick (SK) model and MAX-CUT. The D-Wave quantum annealer outperforms the CIMs on MAX-CUT on cubic graphs. On denser problems, however, we observe an exponential penalty for the quantum annealer [exp(–α DW N 2 )] relative to CIMs [exp(–α CIM N)] for fixed anneal times, both on the SK model and on 50% edge density MAX-CUT. This leads to a several orders of magnitude time-to-solution difference for instances with over 50 vertices. An optimal–annealing time analysis is also consistent with a substantial projected performance difference. The difference in performance between the sparsely connected D-Wave machine and the fully-connected CIMs provides strong experimental support for efforts to increase the connectivity of quantum annealers.

42 ENGINEERING↗

HyKKT

HyKKT (pronounced as "hiked") is a package for solving systems of linear equations of Karush-Kuhn-Tucker (KKT) form, which typically arise in optimization problems, such as optimal power flow analysis. HyKKT uses Cholesky instead of LDL^T factorization and solves the general KKT system to a desired numerical precision via block reduction and conjugate gradient on the Schur complement. Such implementation is more suitable for implementation on graphic processing units (GPUs).

Regev, Shaked↗

CRISPR-CARB/nocap

Network Optimization and Causal Analysis of Perturb-seq (NOCAP) is a software package for causal inference of gene regulation networks using data from perturb-seq.

George, August↗

Wind Turbine Airfoil Design Tools

SAND2025-11738O Wind Turbine Airfoil Design Tools is a software tool that connects existing open-source airfoil analysis tools with optimization software to produce modern airfoil design for wind turbine applications. 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.

Maniaci, David↗

Some Mathematical and Geophysical Considerations in Radioisotope Dating Applications

Some quality considerations for use in isotopic dating are presented to identify and correct heretofore unidentified overestimate scenarios. These include to a lesser degree the statistical interpretation issues with linear-least-squares fitting results but more importantly the isotope effect in the individual components of the isochron coefficient ratios. By taking into consideration the isotope effect (differential mass diffusion rates) when measuring isotopic ratios from very old samples, the distribution dependency in the coefficient ratios will cause a bias if isotopic diffusion rates are not identical throughout a sample. The isotope effect is that isotopes having a smaller atomic mass will diffuse faster throughout a medium than will their heavier counterparts causing concentration gradients of their ratios even when there are no contributions from radioactive decay. The application to Rb/Sr dating is evaluated and shown to result in expected age overestimates when isotopic ratios are employed to linearize the isochron. A suggested method to test for this effect is argued to require rigorous statistical analysis. An associated optimal sampling technique would involve using single-grain etching. It is also shown that the only method to fully eliminate the isotope effect is to not use isotopic ratios at all in radioisotopic dating as the physics do not require the use of isotopic ratios for geochronological dating. However, without the ratios, the data are inherently noisy.

74 ATOMIC AND MOLECULAR PHYSICS↗

SDA: a symbolic differential algebra package in C++

Truncated Power Series Algebra (TPSA), or Differential Algebra (DA), is a well-established tool in accelerator physics, commonly used for generating high-order maps of dynamic systems, as well as in symplectic tracking, normal form analysis, verified integration, optimization, and fast multipole methods. This package is the first to perform symbolic DA computations, enabling traceability of initial condition contributions and runtime reduction for repeated DA calculations, potentially expanding DA’s applications.

97 MATHEMATICS AND COMPUTING↗

DAKOTA JAGUAR User's Manual (V.3.0)

JAGUAR (JAva GUi for Applied Research) is a Java software tool providing an advanced text editor and graphical user interface (GUI) to manipulate DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) input specifications. This document focuses on the features necessary to use JAGUAR.

Adams, Brian M.↗

Final Report

The purpose of this project was to develop tools and techniques to improve the ability of computational scientists to investigate and correct problems (bugs) in their programs. Specifically, the University of Maryland component of this project focused on the problems associated with the finite number of bits available in a computer to represent numeric values. In large scale scientific computation, numbers are frequently added to and multiplied with each other billions of times. Thus even small errors due to the representation of numbers can accumulate into big errors. However, using too many bits to represent a number results in additional computation, memory, and energy costs. Thus it is critical to find the right size for numbers. This project focused on several aspects of this general problem. First, we developed a tool to look for cancelations, the catastrophic loss of precision in numbers due to the addition of two numbers whose actual values are close to each other, but whose representation in a computer is identical or nearly so. Second, we developed a suite of tools to allow programmers to identify exactly how much precision is required for each operation in their program. This tool allows programmers to both verify that enough precision is available, but more importantly find cases where extra precision could be eliminated to allow the program to use less memory, computer time, or energy. These tools use advanced binary modification techniques to allow the analysis of actual optimized code. The system, called Craft, has been applied to a number of benchmarks and real applications.

97 MATHEMATICS AND COMPUTING↗

Abstract Machine Models and Proxy Architectures for Exascale Computing

To achieve exascale computing, fundamental hardware architectures must change. The most significant consequence of this assertion is the impact on the scientific and engineering applications that run on current high performance computing (HPC) systems, many of which codify years of scientific domain knowledge and refinements for contemporary computer systems. In order to adapt to exascale architectures, developers must be able to reason about new hardware and determine what programming models and algorithms will provide the best blend of performance and energy efficiency into the future. While many details of the exascale architectures are undefined, an abstract machine model is designed to allow application developers to focus on the aspects of the machine that are important or relevant to performance and code structure. These models are intended as communication aids between application developers and hardware architects during the co-design process. We use the term proxy architecture to describe a parameterized version of an abstract machine model, with the parameters added to elucidate potential speeds and capacities of key hardware components. These more detailed architectural models are formulated to enable discussion between the developers of analytic models and simulators and computer hardware architects. They allow for application performance analysis and hardware optimization opportunities. In this report our goal is to provide the application development community with a set of models that can help software developers prepare for exascale. In addition, through the use of proxy architectures, we can enable a more concrete exploration of how well new and evolving application codes map onto future architectures. This second version of the document addresses system scale considerations and provides a system-level abstract machine model with proxy architecture information.

97 MATHEMATICS AND COMPUTING↗

ADETS User Manual

ADETS (Automated DEpletion Transport System) calculates coupled neutronic/isotopic results for nuclear systems and produces a large number of criticality and burnup results based on various material feed/removal specifications, power(s), and time intervals. ADETS is a fully automated tool that links the LANL MCNP Monte Carlo transport code with the SCALE system, specifically ORIGEN-ARP (radioactive decay and burnup code). Additionally, ADETS can compute the dose at various distances of the reactor using a point gamma source, whose characteristics are computed by ORIGEN-ARP. In addition, ADETS is fully coupled with the Uncertanty Quantification, Probabilistic Risk Assessment, Parameter Optimization and Data Analysis code RAVEN (developed at the Idaho National Laboratory as well). RAVEN is released with ADETS but MCNP and SCALE (ORIGEN-ARP) are not included.

42 ENGINEERING↗

Low Regeneration Temperature Sorbents for Direct Air Capture of CO 2

Susteon Inc., in partnership with University of Wyoming and SoCalGas, successfully met all major technical objectives to (1) scale up the ionic liquid catalyst for amine-based sorbents for improved desorption and absorption kinetics, (2) evaluate the catalyzed amine-based sorbents for direct CO 2 capture process to determine CO 2 adsorption and desorption rates and energy requirements, and (3) based on the experimental results, develop a conceptual process design to perform a preliminary economic assessment to evaluate the potential for DAC process cost reduction using the catalyzed sorbents. Amine doped solid sorbents are effective for DAC applications and can be regenerated by heat or by a combination of heat, steam, and vacuum. The best sorbent composition identified was polyethyleneimine (PEI) on fumed silica with 200 ppm ionic liquid catalyst. This sorbent formulation was shown to have a CO 2 breakthrough capacity twice that of the non-catalyzed sorbent, in laboratory tests with air at 75% relative humidity (RH). The CO 2 adsorption rate was also 40% higher than that of the non-catalyzed sorbent. This type of sorbents has the attributes required for lowering the overall cost of DAC with high CO 2 capacity and high rate of adsorption. The combination of an industrially utilized amine-based sorbent with a highly active catalyst to form a new class of materials for DAC provides a technically viable pathway for reducing the cost of DAC to <$100/tonne of CO 2 . Laboratory measurements show that the silica/PEI (polyethyleneimine) sorbents with 100 ppm of ionic liquid catalyst have almost 100% higher CO 2 cyclic capacity and 40% higher adsorption rate. Generally, CO 2 desorption occurred at higher temperatures with a rate of desorption 10 times faster than adsorption (which occurred at ambient conditions). Therefore, adsorption rate is a much more important factor in the cost of DAC because it is directly linked to the CAPEX of the total system and the cycle time (i.e., sorbent productivity in ton/day of CO 2 captured per unit volume of the air contactor). An initial process design, coupled with techno-economic analysis, based on optimal experimental results and preliminary resulting from structured sorbent testing, showed a path to lower the DAC cost from the current cost of over $200/tonne CO 2 to less than $100/tonne with a scale-up, mature state of the technology, with projected material and process improvements. These results demonstrate the effectiveness of the catalyst in silica/PEI sorbents in enhancing sorbents’ CO 2 working capacity, in (a) increasing the rate of adsorption and desorption, and (b) in lowering the CAPEX and OPEX of the DAC system employing the ionic liquid catalyzed sorbents.

01 COAL, LIGNITE, AND PEAT↗

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗

EFIT‐AI: Machine Learning and Artificial Intelligence Assisted Equilibrium Reconstruction for Tokamak Experiments and Burning Plasmas (Final Report)

The EFIT-AI project is creating a modern advanced equilibrium reconstruction code suitable for tokamak experiments of burning plasmas. EFIT [1,2] was the first and is the most extensively used equilibrium reconstruction code in the world. This project builds on the production-level experience and adds key elements as follows. 1. A Model Order Reduction (MOR) version of the two-dimensional (2D) Grad-Shafranov equation solver (EFIT-MORNN) using physics-informed neural networks. 2. Improved optimization and data analysis capabilities using a Bayesian framework enhanced with machine learning. 3. A MOR version of the three-dimensional (3D) perturbed equilibrium reconstruction tool.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗