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At least 667 records · Page 37

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

Background: Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design. Results: Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations. Conclusions: PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next generation sequencing, and other experimental protocols targeting highly variable DNA samples.

59 BASIC BIOLOGICAL SCIENCES↗

Technical Note: Multipurpose CT, ultrasound, and MRI breast phantom for use in radiotherapy and minimally invasive interventions

Purpose: To develop a multipurpose gel-based breast phantom consisting of a simulated tumor with realistic imaging properties in CT, ultrasound and MRI, or a postsurgical cavity on CT. Applications for the phantom include: deformable image registration (DIR) quality assurance (QA), autosegmentation validation, and localization testing and training for minimally invasive image-guided procedures such as those involving catheter or needle insertion. Methods: A thermoplastic mask of a typical breast patient lying supine was generated and then filled to make an array of phantoms. The background simulated breast tissue consisted of 32.4 g each of ballistic gelatin (BG) powder and Metamusil™ (MM) dissolved in 800 ml of water. Simulated tumors were added using the following recipe: 12 g of barium sulfate (1.4% v/v) plus 0.000 14 g copper sulfate plus 0.7 g of MM plus 7.2 g of BG all dissolved in 75 ml of water. The phantom was evaluated quantitatively in CT by comparing Hounsfield units (HUs) with actual breast tissue. For ultrasound and MRI, the phantoms were assessed based on subjective image quality and signal-difference to noise (SDNR) ratio, respectively. The stiffness of the phantom was evaluated based on ultrasound elastography measurements to yield an average Young’s modulus. In addition, subjective tactile assessment of phantom was performed under needle insertion. Results: The simulated breast tissue had a mean background value of 24 HU on CT imaging, which more closely resembles fibroglandular tissue (40 HU) as opposed to adipose (−100 HU). The tumor had a mean CT number of 45 HU, which yielded a qualitatively realistic image contrast relative to the background either as an intact tumor or postsurgical cavity. The tumor appeared qualitatively realistic on ultrasound images, exhibiting hypoechoic characteristics compared to background. On MRI, the tumor exhibited a SDNR of 3.7. The average Young’s modulus was computed to be 15.8 ± 0.7 kPa (1 SD). Conclusions: We have developed a process to efficiently and inexpensively produce multipurpose breast phantoms containing simulated tumors visible on CT, ultrasound, and MRI. The phantoms have been evaluated for image quality and elasticity and can serve as a medium for DIR QA, autosegmentation QA, and training for minimally invasive procedures.

60 APPLIED LIFE SCIENCES↗

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗

PMU-Based Decoupled State Estimation for Unsymmetrical Power Systems

Modal decomposition of measurement equations has already been shown to simplify the formulation and resulting computational complexity of three-phase state estimation of systems where all the transmission lines are three-phase and fully transposed. When there are non-transposed and/or mixed-phase lines, modal decomposition can no longer fully decouple the threephase measurement equations. Here, this paper addresses the above shortcoming by proposing a simple yet practical solution based on the commonly used numerical compensation techniques. Thus, it enables application of the powerful decoupling approach to any type of three-phase networks which may contain non-transposed or mixed-phase lines and are fully observable by PMUs. The proposed procedure modifies the measurement set by deriving additive terms that compensate for the neglected unsymmetrical effects. It will be shown that unbalanced systems including nontransposed and mixed-phase elements, can still be transformed into three decoupled subsystems and solved in parallel by the proposed approach. Performance of the proposed algorithm is validated against several IEEE test cases.

42 ENGINEERING↗

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗

LANL Meteorological Program Self-Assessment 2021 Update

This self-assessment, documented in Table 1, has shown that there has been continued significant progress achieved in meeting the intent of the 21 recommendations from the 2015 DMCC Assist Visit. Every year after the Assist Visit, the LANL Met Program has improved, mainly by addressing the recommendations in the Assist Visit report. The Met Program management should continue to strive to apply its limited resources and seek to acquire additional human capital and physical resources to meet the dynamic needs of its growing sitewide customer base. This includes additional upgrading of the hardware and software elements of the Met Program and implementation of its operational procedures and QAPP to ensure it will consistently meet important present program requirements, as well as anticipated future requirements. These improvements have been summarized in the “present improvements and future initiatives” column in Table 1.

47 OTHER INSTRUMENTATION↗

Maximizing the efficiency of plasma-based lepton accelerators

The next generation of particle accelerators will likely rely on compact accelerating structures to achieve very high gradients; one such candidate is accelerators using plasmas for the accelerating structures. Because of the small length scales of these structures, they can also be prone to the beam break-up instability, which would spoil the quality of the beam and leave it unsuitable for many applications. The goal of this project is to develop a framework for understanding the instabilities in plasma accelerators using language from conventional linear accelerator instabilities, such as wake fields and wake functions. During the course of this Phase I, we benchmarked a pseudo-spectral particle-in-cell code to determine its suitability for computing wake functions, and developed a procedure for extracting wake functions from a sequence of simulations using this code.

43 PARTICLE ACCELERATORS↗

Crack opening calculation in phase-field modeling of fluid-filled fracture: A robust and efficient strain-based method

The phase-field method has become popular for the numerical modeling of fluid-filled fractures, thanks to its ability to represent complex fracture geometry without algorithms. However, the algorithm-free representation of fracture geometry poses a significant challenge in calculating the crack opening (aperture) of phase-field fracture, which governs the fracture permeability and hence the overall hydromechanical behavior. Although several approaches have been devised to compute the crack opening of phase-field fracture, they require a sophisticated algorithm for post-processing the phase-field values or an additional parameter sensitive to the element size and alignment. Here, we develop a novel method for calculating the crack opening of fluid-filled phase-field fracture, which enables one to obtain the crack opening without additional algorithms or parameters. Here we transform the displacement-jump-based kinematics of a fracture into a continuous strain-based version, insert it into a force balance equation on the fracture, and apply the phase-field approximation. Through this procedure, we obtain a simple equation for the crack opening which can be calculated with quantities at individual material points. We verify the proposed method with analytical and numerical solutions obtained based on discrete representations of fractures, demonstrating its capability to calculate the crack opening regardless of the element size or alignment.

58 GEOSCIENCES↗

Gaussian approximation potentials for accurate thermal properties of two-dimensional materials

Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. Here, in this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

2D Materials↗

Matrix-free subcell residual distribution for Bernstein finite elements: Monolithic limiting

This paper is focused on the aspects of limiting in residual distribution (RD) schemes for high-order finite element approximations to advection problems. Both continuous and discontinuous Galerkin methods are considered in this work. Discrete maximum principles are enforced using algebraic manipulations of element contributions to the global nonlinear system. The required modifications can be carried out without calculating the element matrices and assembling their global counterparts. The components of element vectors associated with the standard Galerkin discretization are manipulated directly using localized subcell weights to achieve optimal accuracy. Low-order nonlinear RD schemes of this kind were originally developed to calculate local extremum diminishing predictors for flux-corrected transport (FCT) algorithms. In the present paper, we incorporate limiters directly into the residual distribution procedure, which makes it applicable to stationary problems and leads to well-posed nonlinear discrete problems. To circumvent the second-order accuracy barrier, the correction factors of monolithic limiting approaches and FCT schemes are adjusted using smoothness sensors based on second derivatives. Finally, the convergence behavior of presented methods is illustrated by numerical studies for two-dimensional test problems.

97 MATHEMATICS AND COMPUTING↗

"Russians in the Grid" Enrichment Process

Threat intelligence sources are numerous, and the quality of their intelligence is equally variable. The need for quality, actionable, and shareable intelligence is becoming increasingly important as cyber-threats continue to increase. In this paper, we describe the process we used to enrich U.S. CERT’s Technical Alert entitled “Russian Government Cyber-Activity Targeting Energy and Other Critical Infrastructure Sectors,” affectionately referred to as “Russians In the Grid,” from a series of separate but related reports to a final, actionable, unified Structured Threat Information Expression (STIX) v2 representation of the report. In the process, we detail the tools and procedures we used, some of which are automated and others highly manual. We identify some of the limitations of current STIX enrichment tools and techniques, and propose enhancements to allow for more effective enrichment and better overall threat intelligence to be used for more effective threat data-sharing, as well as machine learning-based predictive threat work being conducted at Idaho National Laboratory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Predicting target vessel location on robot-assisted coronary artery bypass graft using CT to ultrasound registration

Purpose: Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon's experience and expertise, and the conversion rate to full sternotomy is in the order of 15%-25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. In this paper, the authors propose a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location, validated via both an in vitro and a clinical study. Methods: As the peri-operative heart migration during RA-CABG has never been reported in the literatures, a simple in vitro validation study was conducted using a heart phantom. To mimic the clinical workflow, a pre-operative CT as well as peri-operative ultrasound images at three different stages in the procedure (Stage{sub 0}--following intubation; Stage{sub 1}--following lung deflation; and Stage{sub 2}--following thoracic insufflation) were acquired during the experiment. Following image acquisition, a rigid-body registration using iterative closest point algorithm with the robust estimator was employed to map the pre-operative stage to each of the peri-operative ones, to estimate the heart migration and predict the peri-operative target vessel location. Moreover, a clinical validation of this technique was conducted using offline patient data, where a Monte Carlo simulation was used to overcome the limitations arising due to the invisibility of the target vessel in the peri-operative ultrasound images. Results: For the in vitro study, the computed target registration error (TRE) at Stage{sub 0}, Stage{sub 1}, and Stage{sub 2} was 2.1, 3.3, and 2.6 mm, respectively. According to the offline clinical validation study, the maximum TRE at the left anterior descending (LAD) coronary artery was 4.1 mm at Stage{sub 0}, 5.1 mm at Stage{sub 1}, and 3.4 mm at Stage{sub 2}. Conclusions: The authors proposed a method to measure and validate peri-operative shifts of the heart during RA-CABG. In vitro and clinical validation studies were conducted and yielded a TRE in the order of 5 mm for all cases. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10-15 mm), our technique suits the clinical requirements. The authors therefore believe this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

GPU-BASED MONTE CARLO DUST RADIATIVE TRANSFER SCHEME APPLIED TO ACTIVE GALACTIC NUCLEI

A three-dimensional parallel Monte Carlo (MC) dust radiative transfer code is presented. To overcome the huge computing-time requirements of MC treatments, the computational power of vectorized hardware is used, utilizing either multi-core computer power or graphics processing units. The approach is a self-consistent way to solve the radiative transfer equation in arbitrary dust configurations. The code calculates the equilibrium temperatures of two populations of large grains and stochastic heated polycyclic aromatic hydrocarbons. Anisotropic scattering is treated applying the Heney-Greenstein phase function. The spectral energy distribution (SED) of the object is derived at low spatial resolution by a photon counting procedure and at high spatial resolution by a vectorized ray tracer. The latter allows computation of high signal-to-noise images of the objects at any frequencies and arbitrary viewing angles. We test the robustness of our approach against other radiative transfer codes. The SED and dust temperatures of one- and two-dimensional benchmarks are reproduced at high precision. The parallelization capability of various MC algorithms is analyzed and included in our treatment. We utilize the Lucy algorithm for the optical thin case where the Poisson noise is high, the iteration-free Bjorkman and Wood method to reduce the calculation time, and the Fleck and Canfield diffusion approximation for extreme optical thick cells. The code is applied to model the appearance of active galactic nuclei (AGNs) at optical and infrared wavelengths. The AGN torus is clumpy and includes fluffy composite grains of various sizes made up of silicates and carbon. The dependence of the SED on the number of clumps in the torus and the viewing angle is studied. The appearance of the 10 {mu}m silicate features in absorption or emission is discussed. The SED of the radio-loud quasar 3C 249.1 is fit by the AGN model and a cirrus component to account for the far-infrared emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Stabilization and Attenuation of Bounded Perturbations in Discrete Control Systems

Necessary and sufficient conditions for the static output feedback stabilization of linear discrete-time control systems are formulated in the form of a matrix inequality. It is shown that the algorithms of stabilization based on these conditions are applicable to a certain class of nonlinear discrete-time control systems. We propose the procedure of construction of the regularities of control guaranteeing the required estimation of the weighted level of attenuation of input signals and initial perturbations, as well as the robust stability of the equilibrium state of the controlled system. A numerical example of the discretetime system of stabilization of a pendulum on a moving platform is presented.

97 MATHEMATICS AND COMPUTING↗

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗

A positivity-preserving and conservative intersection-distribution-based remapping algorithm for staggered ALE hydrodynamics on arbitrary meshes

In this study, we introduce new intersection-distribution-based remapping tools for indirect staggered arbitrary Lagrangian-Eulerian (ALE) simulations of multi-material shock hydrodynamics on arbitrary meshes. In addition to conserving momentum and total energy, the three-stage remapper proposed in this work preserves non-negativity of the internal energy. At the first stage, we construct slope-limited piecewise-linear reconstructions of all conserved quantities on zones of the source mesh and perform intersection-based remap to obtain bound-preserving zonal quantities on the target mesh. At the second stage, we define bound-preserving nodal quantities of the staggered ALE discretization as convex combinations of corner quantities. The nodal internal energy is corrected in a way which keeps it non-negative, while providing exact conservation of total energy. At the final stage, we distribute the non-negative nodal internal energy to corners, zones and materials using non-negative weights. Proofs of positivity preservation are provided for each stage. This work is a natural extension of our paper [14] in which a similar intersection-distribution-based remapping procedure was employed. The original version used a nodal kinetic energy fix which did not provably ensure positivity preservation for the zonal internal energy after the final distribution stage. The new algorithm cures this potential drawback by using ‘coordinated’ limiters for piecewise-linear reconstructions, remapping the internal energy to nodes and correcting it before redistribution. The effectiveness of the new nodal fix is illustrated by numerical examples.

97 MATHEMATICS AND COMPUTING↗

Supercharging simulation-based inference for Bayesian optimal experimental design

Abstract Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG maximization and show that a simple multi-start parallel gradient ascent procedure can substantially improve reliability and performance. With these innovations, our SBI-based BOED methods are able to match or outperform by up to 22% existing state-of-the-art approaches across standard BOED benchmarks.

97 MATHEMATICS AND COMPUTING↗

Structural features of sodium silicate glasses from reactive force field-based molecular dynamics simulations

Atomistic computer simulations can offer insights into silicate glass-environment interactions with the recent development of reactive potentials. Yet, the accuracy of generated glass structures with these potential was usually not fully examined. In this paper, the capability of the reactive force field (ReaxFF) to describe the short and medium range structure features of sodium silicate glasses in molecular dynamics simulations is investigated by comparing a widely used partial charge pairwise potential and available experimental data. Glass structure information such as pair distribution function (PDF), coordination number, Qn species, neutron broadened structure factor, and X-ray broadened structure factor of the glass structures from ReaxFF simulations were calculated and compared to evaluate the generated glass structure. Advantages and limitations of the potentials and glass forming procedures, as well as areas of further improvement, were discussed. The results show that the recently refined ReaxFF parameters through the proposed procedure enable the simulations of sodium silicate glass structures with minimal defects, which paves the way to investigate water-glass interaction mechanisms with the reactive enabled potentials.

36 MATERIALS SCIENCE↗