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At least 1,657 records · Page 92

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗

Air compressor load forecasting using artificial neural network

Air compressor systems are responsible for approximately 10% of the electricity consumed in United States and European Union industry. As many researches have proven the effectiveness of using Artificial Neural Network inair compressor performance prediction, there is still a need to forecast the air compressor electrical load profile. The objective of this study is to predict compressed air systems’ electrical load profile, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load managementand look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Networkand Long Short-Term Memory were used to predict an air compressors electrical load. Compressors with three different control mechanisms are evaluated with a total number of 11,874 observations. Here, the forecasts were validated using out-of-sample datasets with 5-fold cross-validation. Models produced average coefficient ofdetermination values from 0.24 to 0.94, average root-mean-square errors from 0.05 kW - 5.83 kW, and meanabsolute scaled errors from 0.20 to 1.33. The results indicate that both artificial neural networks yield goodresults for compressors using variable speed drive (average R 2 = 0.8 and no naïve forecasting), only the longshort-term memory model gives acceptable results for compressors using on/off control (average R 2 = 0.82 and no naïve forecasting), and no satisfactory results are obtained for load/unload type air compressors (models constituting active forecasting).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

rcsb-api : Python Toolkit for Streamlining Access to RCSB Protein Data Bank APIs

The Protein Data Bank (PDB) was founded in 1971 as the first open-access digital data resource in biology to serve as the single global archive for three-dimensional (3D) macromolecular structure data. Current PDB holdings exceed 230,000 experimentally determined structures of proteins, nucleic acids, viruses, and macromolecular machines. The RCSB Protein Data Bank RCSB.org research-focused web portal facilitates search, analyses, and visualization of every PDB structure along with more than one million Computed Structure Models from AlphaFold DB and the ModelArchive. It is powered by a set of publicly available Application Programming Interfaces (APIs) that both support RCSB.org users and provide programmatic access to PDB data. Given the breadth and levels of granularity encompassed in this rich data collection, efficiently accessing the information programmatically may be challenging for new users. RCSB PDB has developed a Python software package, rcsb-api , that facilitates easy and efficient use of RCSB PDB APIs within a Python environment. This software tool is designed to streamline access to the extensive corpus of data housed within the PDB, enabling researchers to search, retrieve, and analyze 3D biostructure data seamlessly. Its use will accelerate research in structural biology, molecular biology and biochemistry, drug discovery, and bioinformatics by providing more efficient tools for data integration and analysis. The new toolkit is available on GitHub (github.com/rcsb/py-rcsb-api) and published to the public Python package repository (PyPI) to foster wider usage and support basic and applied research in fundamental biology, biomedicine, and the energy sciences.

FAIR principles↗

Method for measurement of TRISO kernel and layer volumes by X-ray computed tomography

Layer dimensions are key parameters for as-fabricated tristructural-isotropic (TRISO) particle fuel as well as for post-irradiation examination of particle performance. Layer thicknesses are typically measured by optical microscopy of the particle cross section near mid-plane, while layer volumes are estimated with serial sectioning and microscopy. This method for measuring layer volumes is limited due to the resolution limit imposed by slice thickness and the effect of the polishing process on delicate irradiated particle microstructures. In this study, image processing software has been developed to segregate the three-dimensional (3D) TRISO particle images provided by x-ray computed tomography (XCT) into high-resolution volumetric data for the kernel, all particle layers, and any internal voids introduced during irradiation. These data can be used to analyze key in-reactor behaviors of TRISO particles such as kernel swelling or buffer shrinkage, which are important inputs for fuel performance modeling.

36 MATERIALS SCIENCE↗

Towards elastic in situ analysis for high-performance computing simulations

In situ analysis and visualization have grown increasingly popular for enabling direct access to data from high-performance computing (HPC) simulations. As a simulation progresses and interesting physical phenomena emerge, however, the data produced may become increasingly complex, and users may need to dynamically change the type and scale of in situ analysis tasks being carried out and consequently adapt the amount of resources allocated to such tasks. To date, none of the production in situ analysis frameworks offer such an elasticity feature, and for good reason: the assumption that the number of processes could vary during run time would force developers to rethink software and algorithms at every level of the in situ analysis stack. In this paper we present Colza, a data staging service with elastic in situ visualization capabilities. We demonstrate the use of Colza with the Deep Water Impact and the AMR-Wind simulations, coupling them with the ParaView Catalyst and Ascent in situ libraries, and show that Colza enables dynamic rescaling of these widely-used frameworks with no interruption to the simulation or staging service. Here, we highlight the challenges of enabling such elasticity, which requires overcoming these frameworks' reliance on MPI, using distinct engineering approaches, namely dependency injection and dependency overload. To the best of our knowledge, this work is the first to enable elastic in situ visualization capabilities for HPC applications on top of existing production analysis tools.

97 MATHEMATICS AND COMPUTING↗

Oncentra brachytherapy planning system

In modern cancer management, treatment planning has progressed as a contemporary tool with all the advances in computing power in recent years. One of the advanced planning tools uses 3-dimensional (3D) data sets for accurate dose distributions in patient prescription. Among these planning processes, brachytherapy has been a very important part of a successful cancer management program, offering clinical benefits with specific or combined treatments with external beam therapy. In this chapter, we mainly discussed the Elekta Oncentra planning system, which is the main treatment planning tool for high-dose rate (HDR) modality in our facility and in many other facilities in the United States. HDR is a technically advanced form of brachytherapy; a high-intensity radiation source (3.6 mm in length) is delivered with step motor in submillimeter precision under computer guidance directly into the tumor areas while minimizing injury to surrounding normal healthy tissue. Oncentra planning is the key component to generate a deliverable brachytherapy procedure, which is executed on the microSelectron V3 remote afterloader treatment system. Creating a highly conformal plan can be a time-consuming task. The development of Oncentra software (version 4.5.3) offers a variety of useful tools that facilitate many of the clinical challenging tasks for planning, such as contouring and image reconstruction, as well as rapid planning calculations with dose and dose volume histogram analysis. Oncentra Brachy module creates workflow and optimizes the planning accuracy for wide varieties of clinical HDR treatments, such as skin, gynecologic (GYN), breast, prostate, and many other applications. The treatment file can also be transferred to the afterloader control station for speedy delivery. The design concept, calculation algorithms, and optimization modules presented some key characteristics to plan and treat the patients effectively and accurately. The dose distribution and accuracy of several clinical sample cases were discussed to illustrate the effectiveness and clinical efficacy. The American Association of Physicists in Medicine brachytherapy reports of TG-43 and TG-186 were also described and compared in evaluations of fundamental calculation methodologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Bridging the Gap between the X-ray Absorption Spectroscopy and the Computational Catalysis Communities in Heterogeneous Catalysis: A Perspective on the Current and Future Research Directions

X-ray absorption spectroscopy (XAS) [extended X-ray absorption fine structure (EXAFS) and X-ray absorption near-edge structure (XANES)] is a key technique within the heterogeneous catalysis community to probe the structure and properties of the active site(s) for a diverse range of catalytic materials. Furthermore, the interpretation of the raw experimental data to derive an atomistic picture of the catalyst requires modeling and analysis; the EXAFS data are compared to a model, and a goodness of fit parameter is used to judge the best fit. This EXAFS modeling can often be nontrivial and time-consuming; overcoming or improving these limitations remains a central challenge for the community. Considering these limitations, this Perspective highlights how recent developments in analysis software, increased availability of reliable computational models, and application of data science tools can be used to improve the speed, accuracy, and reliability of EXAFS interpretation. In particular, we emphasize the advantages of combining theory and EXAFS as a unified technique that should be treated as a standard (when applicable) to identify catalytic sites and not two separate complementary methods. Building on the recent trends in the computational catalysis community, we also present a community-driven approach to adopt FAIR Guiding Principles for the collection, analysis, dissemination, and storage of XAS data. Written with both the experimental and theory audience in mind, we provide a unified roadmap to foster collaborations between the two communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative study of laminar and turbulent flow model with different operating parameters for radio frequency-inductively coupled plasma torch working at 3 MHz frequency at atmospheric pressure

This paper provides 2D comparative study of results obtained using laminar and turbulent flow model for RF (radio frequency) Inductively Coupled Plasma (ICP) torch. The study was done for the RF-ICP torch operating at 50 kW DC power and 3 MHz frequency located at BARC. The numerical modeling for this RF-ICP torch is done using ANSYS software with the developed User Defined Function. A comparative study is done between laminar and turbulent flow model to investigate how temperature and flow fields change when using different operating conditions such as (a) swirl and no swirl velocity for sheath gas flow rate, (b) variation in sheath gas flow rate, and (c) variation in plasma gas flow rate. These studies will be useful for different material processing applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High speed finite element simulations on the graphics card

A software package is developed to perform explicit time domain finite element simulations of ultrasonic propagation on the graphical processing unit, using Nvidia’s CUDA. Of critical importance for this problem is the arrangement of nodes in memory, allowing data to be loaded efficiently and minimising communication between the independently executed blocks of threads. The initial stage of memory arrangement is partitioning the mesh; both a well established ‘greedy’ partitioner and a new, more efficient ‘aligned’ partitioner are investigated. A method is then developed to efficiently arrange the memory within each partition. The technique is compared to a commercial CPU equivalent, demonstrating an overall speedup of at least 100 for a non-destructive testing weld model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A home-made system for IPCE measurement of standard and dye-sensitized solar cells

A home-made system for incident photon-to-electron conversion efficiency (IPCE) characterization, based on a double-beam UV-Vis spectrophotometer, has been set up. In addition to its low cost (compared to the commercially available apparatuses), the double-beam configuration gives the advantage to measure, autonomously and with no need for supplementary equipment, the lamp power in real time, compensating possible variations of the spectral emission intensity and quality, thus reducing measurement times. To manage the optical and electronic components of the system, a custom software has been developed. Validations carried out on a common silicon-based photodiode and on a dye-sensitized solar cell confirm the possibility to adopt this system for determining the IPCE of solar cells, including dye-sensitized ones.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Charged particle tracking through electrostatic wire meshes using the finite element method

Wire meshes are used across many disciplines to accelerate and focus charged particles, however, analytical solutions are non-exact and few codes exist which simulate the exact fields around a mesh with physical sizes. A tracking code based in Matlab-Simulink using field maps generated using finite element software has been developed which tracks electrons or ions through electrostatic wire meshes. The fields around such a geometry are presented as an analytical expression using several basic assumptions, however, it is apparent that computational calculations are required to obtain realistic values of electric potential and fields, particularly when multiple wire meshes are deployed. The tracking code is flexible in that any quantitatively describable particle distribution can be used for both electrons and ions as well as other benefits such as ease of export to other programs for analysis. The code is made freely available and physical examples are highlighted where this code could be beneficial for different applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides

The pursuit of more advanced electronics, and finding solutions to energy needs often hinges upon the discovery and optimization of new functional materials. However, the discovery rate of these materials is alarmingly low. Much of the information that could drive this rate higher is scattered across tens of thousands of papers in the extant literature published over several decades but is not in an indexed form, and cannot be used in entirety without substantial effort. Many of these limitations can be circumvented if the experimentalist has access to systematized collections of prior experimental procedures and results. Here, we investigate the property-processing relationship during growth of oxide films by pulsed laser deposition. To do so, we develop an enabling software tool to (1) mine the literature of relevant papers for synthesis parameters and functional properties of previously studied materials, (2) enhance the accuracy of this mining through crowd sourcing approaches, (3) create a searchable repository that will be a community-wide resource enabling material scientists to leverage this information, and (4) provide through the Jupyter notebook platform, simple machine-learning-based analysis to learn the complex interactions between growth parameters and functional properties. Here, the results allow visualization of growth windows, trends and outliers, which can serve as a template for analyzing the distribution of growth conditions, provide starting points for related compounds and act as a feedback for first-principles calculations. Such tools will comprise an integral part of the materials design schema in the coming decade.

36 MATERIALS SCIENCE↗

Toward 3D data visualization using virtual reality tools

Virtual Reality (VR) offers the opportunity to display data, instrumentation, and experimental setups in three dimensions and gives the user the ability to interact with the objects. This technology moves visualization beyond two-dimensional projections on a flat screen with a fixed field of view in which a keyboard or another similar controller is needed to change the view. Advances in both hardware and software for VR make it possible for the non-expert to develop visualization tools for scientific applications both for viewing and for sharing data or diagnostic hardware between users in three dimensions. Furthermore, this manuscript describes application development using two VR software tools, Unity gaming engine and A-frame, for visualizing data and high energy physics targets.

47 OTHER INSTRUMENTATION↗

Analysis of Radiation Transport Due to Activated Coolant in the ITER Neutral Beam Injection Cell

Detailed spatial distributions of the biological dose rate due to a variety of sources are required for the design of the ITER tokamak facility to ensure that all radiological zoning limits are met. During operation, water in the Integrated loop of Blanket, Edge-localized mode and vertical stabilization coils, and Divertor (IBED) cooling system will be activated by plasma neutrons and will flow out of the bioshield through a complex system of pipes and heat exchangers. This paper discusses the methods used to characterize the biological dose rate outside the tokamak complex due to 16 N gamma radiation emitted by the activated coolant in the Neutral Beam Injection (NBI) cell of the tokamak building. Activated coolant will enter the NBI cell through the IBED Primary Heat Transfer System (PHTS), and the NBI PHTS will also become activated due to radiation streaming through the NBI system. To properly characterize these gamma sources, the production of 16 N, the decay of 16 N, and the flow of activated water through the coolant loops were modeled. The impact of conservative approximations on the solution was also examined. Once the source due to activated coolant was calculated, the resulting biological dose rate outside the north wall of the NBI cell was determined through the use of sophisticated variance reduction techniques. The AutomateD VAriaNce reducTion Generator (ADVANTG) software implements methods developed specifically to provide highly effective variance reduction for complex radiation transport simulations such as those encountered with ITER. Using ADVANTG with the Monte Carlo N-particle (MCNP) radiation transport code, radiation responses were calculated on a fine spatial mesh with a high degree of statistical accuracy. In conclusion, advanced visualization tools were also developed and used to determine pipe cell connectivity, to facilitate model checking, and to post-process the transport simulation results.

59 BASIC BIOLOGICAL SCIENCES↗

Supernova neutrino detection in NOvA

The NOvA long-baseline neutrino experiment uses a pair of large, segmented, liquid-scintillator calorimeters to study neutrino oscillations, using GeV-scale neutrinos from the Fermilab NuMI beam. These detectors are also sensitive to the flux of neutrinos which are emitted during a core-collapse supernova through inverse beta decay interactions on carbon at energies of &calO;(10 MeV). This signature provides a means to study the dominant mode of energy release for a core-collapse supernova occurring in our galaxy. We describe the data-driven software trigger system developed and employed by the NOvA experiment to identify and record neutrino data from nearby galactic supernovae. This technique has been used by NOvA to self-trigger on potential core-collapse supernovae in our galaxy, with an estimated sensitivity reaching out to 10 kpc distance while achieving a detection efficiency of 23% to 49% for supernovae from progenitor stars with masses of 9.6 M⊙ to 27 M⊙, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗

Numerical modelling of impact seismic sources using the stress glut theory

SUMMARY Meteorite impacts have proved to be a significant source of seismic signal on the Moon, and have now been recorded on Mars by InSight seismometers. Understanding how impacts produce seismic signal is key to the interpretation of this unique data, and to improve their identification in continuous seismic records. Here, we use the seismic Representation Theorem, and particularly the stress glut theory, to model the seismic motion resulting from impact cratering. The source is described by equivalent forces, some resulting from the impactor momentum transfer, and others from the stress glut, which represents the mechanical effect of plasticity and non linear processes in the source region. We condense these equivalent forces into a point-source with a time-varying single force and nine-component moment tensor. This analytical representation bridges the gap between the complex dynamics of crater formation, and the linear point-source representation classically used in seismology. Using the multiphysics modelling software HOSS, we develop a method to compute the stress glut of an impact, and the associated point-source from hypervelocity impact simulations. For a vertical and an oblique impact at 1000 m s−1, we show that the moment tensor presents a significant deviatoric component. Hence, the source is not an ideal isotropic explosion contrary to previous assumptions, and draws closer to a double couple for the oblique impact. The contribution of the point force to the seismic signal appears negligible. We verify this model by comparing two signals: (1) HOSS is coupled to SPECFEM3D to propagate the near-source signal elastically to remote seismic stations; (2) the point-source model derived from the stress-glut theory is used to generate displacements at the same distance. The comparison shows that the point-source model is accurately simulating the low-frequency impact seismic waveform, and its seismic moment is in trend with Lunar and Martian impact data. High-frequencies discrepancies exist, which are partly related to finite-source effects, but might be further explained by the difference in mathematical framework between classical seismology and HOSS’ numerical modelling.

79 ASTRONOMY AND ASTROPHYSICS↗