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ParelastiFWl is a python-based frontend to the seismic full waveform inversion process using Sandia Geophysics Department's 3-D isotropic elastic full waveform simulation code, Parelasti. The arguments one provides to ParelastiFWl guide the full waveform inversion process, including resolution of the inversion grid and basic regularization. This report outlines the user flags and ParelastiFWI usage to control the full waveform inversion procedure.
PNNL cybersecurity experts developed two novel cyber tools to help utilities and organizations that serve them combat malicious cyber attacks. The first is the Cybersecurity Framework Tool, or CFT. This patented tool provides a way for utilities and their associated vendors to identify, protect, detect, respond to, and recover from emerging cyber threats or vulnerabilities to critical infrastructure. CFT provides an easy-to-follow set of best practices, policies, and procedures to improve the cybersecurity postures of critical infrastructure. The second tool is the Cybersecurity Training Game Simulator, a dynamic “train the trainer” tool. The game provides interactive training scenarios based on major cyberattacks that happened in the U.S. during the past decade. Both innovations are available for commercialization. Contact Commercialization Manager Peter Christensen at peter.christensen@pnnl.gov to learn more.
A generalization of vector fields, referred to as N-direction fields or cross fields when N=4, has been recently introduced and studied for geometry processing, with applications in quadrilateral (quad) meshing, texture mapping, and parameterization. We make the observation that cross field design for two-dimensional quad meshing is related to the well-known Ginzburg-Landau problem from mathematical physics. This identification yields a variety of theoretical tools for efficiently computing boundary-aligned quad meshes, with provable guarantees on the resulting mesh, for example, the number of mesh defects and bounds on the defect locations. The procedure for generating the quad mesh is to (i) find a complex-valued "representation" field that minimizes the Dirichlet energy subject to a boundary constraint, (ii) convert the representation field into a boundary-aligned, smooth cross field, (iii) use separatrices of the cross field to partition the domain into four sided regions, and (iv) mesh each of these four-sided regions using standard techniques. Under certain assumptions on the geometry of the domain, we prove that this procedure can be used to produce a cross field whose separatrices partition the domain into four sided regions. To solve the energy minimization problem for the representation field, we use an extension of the Merriman-Bence-Osher (MBO) threshold dynamics method, originally conceived as an algorithm to simulate motion by mean curvature, to minimize the Ginzburg-Landau energy for the optimal representation field. Lastly, we demonstrate the method on a variety of test domains.
Purpose: To calculate the ablation volume of percutaneous cryoablation (PCA) with a two-cryo-probe technique for small hepatocellular carcinomas (HCCs) and to assess risk factors for local tumor recurrence (LTR). Materials and Methods: Between January 2013 and June 2017, 96 patients (mean age, 60.7 years; range, 37–83 years) with 106 small HCCs were retrospectively analyzed. The ablation volume, technical success, LTR rates, and complications were evaluated. Ablation volume was measured after the first freezing and immediately after completing PCA twice via computed tomography imaging. Prognostic factors associated with LTR were analyzed. Results: Technical success was achieved in all patients. The mean final ablation volume was 19.1 ± 4.8 cm{sup 3}, which was significantly higher than the first freezing ablation volume (14.7 ± 4.3 cm{sup 3}, p < 0.001). During the median follow-up period of 16.7 months (range, 5–52 months), LTR-free survival rates based on Kaplan–Meier analyses at 6 months, 1 year, and 2 years were 87.7%, 84.0%, and 80.2%, respectively. Only one major complication of post-procedural arterial bleeding occurred. A final ablation volume/tumor volume < 10 was a significant risk factor for LTR (p = 0.044). Conclusions: A ratio of final ablation volume to tumor volume < 10 was a significant prognostic factor for LTR. Therefore, the measurement and prediction of the final ablation volume are important to reduce LTR.
For many plasma physics problems, three-dimensional and kinetic effects are very important. However, such simulations are very computationally intensive. Fortunately, there is a class of problems for which there is nearly azimuthal symmetry and the dominant three-dimensional physics is captured by the inclusion of only a few azimuthal harmonics. Recently, it was proposed [1] to model one such problem, laser wakefield acceleration, by expanding the fields and currents in azimuthal harmonics and truncating the expansion. The complex amplitudes of the fundamental and first harmonic for the fields were solved on an r–z grid and a procedure for calculating the complex current amplitudes for each particle based on its motion in Cartesian geometry was presented using a Marder's correction to maintain the validity of Gauss's law. In this paper, we describe an implementation of this algorithm into OSIRIS using a rigorous charge conserving current deposition method to maintain the validity of Gauss's law. We show that this algorithm is a hybrid method which uses a particles-in-cell description in r–z and a gridless description in ϕ. We include the ability to keep an arbitrary number of harmonics and higher order particle shapes. Examples for laser wakefield acceleration, plasma wakefield acceleration, and beam loading are also presented and directions for future work are discussed.
Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.
The concept of constructing precision laser goniometer systems, based on integrating a ring laser and an optical angle sensor with the holographic principle of angular scale recording is considered. The concept implies the application of the cross-calibration procedure, aimed at determination of systematic components of the errors of angle sensors, used in the system. The results of the presented system studies demonstrate the error of angular measurements amounting to {approx}0.01''. The results of implementing the proposed concept in the creation of a standard system of the plane angle unit of rigid rotation and the measuring and computing complex for automated control of digital angle transducers with high digit capacity are briefly presented. (laser optics 2012)
Purpose: In proton double-scattering radiotherapy, compensators are the essential patient specific devices to contour the distal dose distribution to the tumor target. Traditional compensator QA is limited to checking the drilled surface profiles against the plan. In our work, a compensator QA process was established that assess the entire compensator including its internal structure for patient 3D dose verification. Methods: The fabricated patient compensators were CT scanned. Through mathematical image processing and geometric transformations, the CT images of the proton compensator were combined with the patient simulation CT images into a new series of CT images, in which the imaged compensator is placed at the planned location along the corresponding beam line. The new CT images were input into the Eclipse treatment planning system. The original plan was calculated to the combined CT image series without the plan compensator. The newly computed patient 3D dose from the combined patientcompensator images was verified against the original plan dose. Test plans include the compensators with defects intentionally created inside the fabricated compensators. Results: The calculated 3D dose with the combined compensator and patient CT images reflects the impact of the fabricated compensator to the patient. For the test cases in which no defects were created, the dose distributions were in agreement between our method and the corresponding original plans. For the compensator with the defects, the purposely changed material and a purposely created internal defect were successfully detected while not possible with just the traditional compensator profiles detection methods. Conclusion: We present here a 3D dose verification process to qualify the fabricated proton double-scattering compensator. Such compensator detection process assesses the patient 3D impact of the fabricated compensator surface profile as well as the compensator internal material and structure changes. This research receives funding support from CURA Medical Technologies.
Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here, we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.
We present an alternative method for carrying out a principal-component analysis of Wilson coefficients in standard model effective field theory (SMEFT). The method is based on singular-value decomposition (SVD). The SVD method provides information about the sensitivity of experimental observables to physics beyond the standard model that is not accessible in the Fisher-information method. In principle, the SVD method can also have computational advantages over diagonalization of the Fisher information matrix. We demonstrate the SVD method by applying it to the dimension-6 coefficients for the process of top-quark decay to a b quark and a W boson and use this example to illustrate some pitfalls in widely used fitting procedures. We also outline an iterative procedure for applying the SVD method to dimension-8 SMEFT coefficients.
Graphics processing units (GPUs) have rapidly emerged as a very significant player in high performance computing. Single instruction multiple thread (SIMT) pipelines are typically used in GPUs to exploit parallelism and maximize performance. Although support for unstructured control flow has been included in GPUs, efficiently managing thread divergence for arbitrary parallel programs remains a critical challenge. In this paper, we focus on the problem of supporting recursion in modern GPUs. We design and comparatively evaluate various algorithms to manage thread divergence encountered in recursive programs. The results improve upon traditional post-dominator based reconvergence mechanisms designed to handle thread divergence due to control flow within a procedure.
Emerging HPC systems are expected to be deployed with an unprecedented level of complexity, due to a deep system memory/storage hierarchy and heterogeneity of the storage hardware. This hierarchy is expected to range from CPU cache through several levels of volatile memory to nonvolatile memory, traditional hard disks, and tape. Simple and efficient methods of data management and movement through this hierarchy is critical for scientific applications using exascale systems. Existing storage system and I/O (SSIO) technologies face severe challenges in dealing with these requirements. POSIX and MPI I/O standards that are the basis for existing I/O libraries and parallel file systems present fundamental challenges in the areas of scalable metadata operations, semantics-based data movement performance tuning, asynchronous operation, and support for scalable consistency of distributed operations. Moving toward new paradigms for SSIO in the extreme-scale era, we have proposed to investigate novel object-based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these overarching goals, we initiated an effort to develop a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-centric manner. Managing data as objects enables powerful optimization opportunities for data movement and transformations. The R&D focus of this project are: 1) formulation of object-oriented PDCs and their mapping in different levels of the exascale storage hierarchy; 2) efficient strategies for moving data in deep storage hierarchies using PDCs; 3) techniques for transforming and reorganizing data based on application requirements; and 4) novel analysis paradigms for enabling data transformations and user-defined analysis on data in PDCs. Toward achieving these overarching goals, we designed an object-centric application programing interface (API) for HPC, scalable metadata management for object-centric storage systems, and data movement optimizations such as Data Elevator for moving data between two levels of storage devices and TAPIOCA for efficient aggregation of data on compute nodes. We then implemented several components of the PDC system. They include metadata management, data placement services, remote procedure calls, data aggregation, etc. We have put them together into the overall PDC framework.
Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.
PurposeThe aim of this study was to evaluate the feasibility of cone-beam computed tomography (CBCT)-based real-time 3-D guidance of TIPSS placement and its positioning compared to standard guiding methods.Materials and MethodsIn a prospective, randomized, consecutive study design from 2015 to 2017, we included 21 patients in the CBCT guided group and 15 patients in the ultrasound (US) guided group. The prospective groups were compared in terms of success rate of intervention, portal vein puncture/procedure time, number of puncture attempts and applied dose. We furthermore retrospectively analyzed the last 23 consecutive cases with fluoroscopic guided portal vein puncture in terms of success rate, procedure time and applied dose, as it has been the standard method before US guidance.ResultsThe median number of puncture attempts (CBCT: n = 2, US: n = 4, p = 0.249) and the mean puncture time (CBCT: 32 ± 45 min, US: 36 ± 45 min, p = 0.515) were not significantly different. There were furthermore no significant differences in the mean time needed for the total TIPSS procedure (CBCT: 115 ± 52 min, US: 112 ± 41 min, fluoroscopy: 110 ± 33 min, p = 0.996). The mean applied dose of the complete procedure also showed no statistically significant differences (CBCT: 563 ± 289 Gy·cm{sup 2}, US: 322 ± 186 Gy·cm{sup 2}, fluoroscopy: 469 ± 352 Gy·cm{sup 2}, p = 0.069). There were no image guidance related complications.ConclusionReal-time 3-D needle guidance based on CBCT is feasible for TIPSS placement. In terms of puncture attempts, duration and dose, CBCT guidance was not inferior to the control groups and may be a valuable support for interventionists in TIPSS procedures.
X-ray Photoelectron Spectroscopy of large bandgap or insulating material surfaces relies on an effective mechanism that compensates for the emission (loss) of electrons by maintaining the material surface at a steady-state uniform potential. While a steady-state may be attained by utilizing an active compensation, such as low power electron emitting filament, there is the possibility that the surface potential is not uniform over the area analyzed, leading to peak shifts and incorrect spectral interpretation. Here, in this work, a spectral data processing method based on mapping the ZrO 2 and Pd/ZrO 2 surfaces utilizing photoemission peak binding energy is proposed, which provides information about the response of specific material surfaces to charge compensation. Spectromicroscopy of ZrO 2 and Pd/ZrO 2 surfaces without spatial information is used to monitor the efficacy of charge compensation. Exploiting counts distributed over many bins require the use of procedures and algorithms essential to practical mapping peak positions. Iterative singular value decomposition is therefore introduced and utilized as a means of efficiently delivering spatially resolved spectra from which binding energy for peaks is computed. The concepts developed in this work result in robust and accurate peak models of ZrO 2 and Pd/ZrO 2 that can be applied in XPS analysis of not only ZrO 2 but other large bandgap or insulating material surfaces. Supporting arguments for a peak model representing signal from Zr 3p and Pd 3d are developed within this work are presented.
The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed. While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Here, starting with 70 150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.
Observations of high-redshift galaxies with unprecedented detail have now been rendered possible with the James Webb Space Telescope (JWST). However, accurately quantifying their morphology remains uncertain due to potential biases and uncertainties. To address this issue, we used a sample of 1816 nearby DESI galaxies, with a stellar mass range of 10 9.75 - 11.25 M ⊙ , to compute artificial images of galaxies of the same mass located at 0.75 ≤ z ≤ 3 and observed at rest-frame optical wavelength in the Cosmic Evolution Early Release Science (CEERS) survey. We analyzed the effects of cosmological redshift on the measurements of Petrosian radius (R p ), half-light radius (R 50 ), asymmetry (A), concentration (C), axis ratio (q), and Sérsic index (n). Our results show that R p and R 50 , calculated using non-parametric methods, are slightly overestimated due to PSF smoothing, while R 50 , q, and n obtained through fitting a Sérsic model does not exhibit significant biases. By incorporating a more accurate noise effect removal procedure, we improve the computation of A over existing methods, which often overestimate, underestimate, or lead to significant scatter of noise contributions. Due to PSF asymmetry, there is a minor overestimation of A for intrinsically symmetric galaxies. However, for intrinsically asymmetric galaxies, PSF smoothing dominates and results in an underestimation of A, an effect that becomes more significant with higher intrinsic A or at lower resolutions. Moreover, PSF smoothing also leads to an underestimation of C, which is notably more pronounced in galaxies with higher intrinsic C or at lower resolutions. We developed functions based on resolution level, defined as R p /FWHM, for correcting these biases and the associated statistical uncertainties. Applying these corrections, we measured the bias-corrected morphology for the simulated CEERS images and we find that the derived quantities are in good agreement with their intrinsic values – except for A, which is robust only for angularly large galaxies where R p /FWHM ≥ 5. Our correction functions can be applied to other surveys, offering valuable tools for future studies.
Hyperthermia (42-46°C), treatment of tumor tissue through elevated temperature, offers several advantages including high cost-effectiveness, highly targeted ablation and fewer side effects and hence higher safety level over traditional therapies such as chemotherapy and radiotherapy. Recently, hyperthermia using heat release through exothermic acid-base neutralization comes into view owing to its relatively safe products of salt and water and highly confined ablation. However, lack of quantitative understanding of the spatial and temporal temperature profiles that are produced by simultaneous diffusion of liquid chemical and its chemical reaction within tumor tissue impedes the application of this method. This article is dedicated to quantify thermal ablation effects of acid and base both individually and as in neutralization via infrared captured thermal images. A theoretical model is used to approximate specific heat absorption rate (SAR) based on experimental measurements that contrast two types of tissue, normal pork and pig liver. According to the computation, both pork and liver tissue has a higher ability in absorbing hydrochloric acid (HCl) than sodium hydroxide, hence suggesting that a reduced dosage for HCl is appropriate in a surgery. The heating effect depends heavily on the properties of tissue types and amount of chemical reagents administered. Given thermal parameters such as SAR for different tissues, a computational model can be made in predicting temperature transitions which will be helpful in planning and optimizing surgical hyperthermia procedures.