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DOE OSTI2022

Inorganometallic Catalyst Design Center (ICDC) EFRC Accomplishments

The ICDC focused largely on heterogeneous catalysis of oxidative chemical transformations, especially those that came to prominence as natural gas (wet shale gas) supplanted crude oil as the primary feedstock in North America for carbon-based manufacturing of commodity chemicals. Driven by fracking-enabled access to enormous stores of shale-trapped wet gas, the feedstock change from oil to gas enabled a shift away from high-temperature catalytic breakdown of large hydrocarbons to catalytic build-up of C4, C3, C2, and C1 into desired intermediates, but now at much more modest temperatures. In turn, the much lower thermal force accompanying these kinds of reactions facilitates catalyst stabilization and characterization, including operando characterization, while slowing on-stream catalyst evolution (i.e., preserving catalyst structure), accommodating catalyst complexity, and enabling creation of uniform arrays of heterogeneous catalysts with single-atom or near-single-atom precision—at least for model systems. Together these features have proven to be a boon to hypothesis-driven catalysis science and to experimentally testable computation-based design advances and mechanism explication. The ICDC has greatly facilitated the integration of catalyst synthesis, advanced characterization, performance assessment, and computational elucidation—with advances in each of these realms spurring achievements in catalysis science and complementary realms.

03 NATURAL GAS↗
DOE OSTI2014

WE-G-16A-01: Evolution of Radiation Treatment Planning

Welcome and Introduction - Lawrence N. Rothenberg This symposium is one a continuing series of presentations at AAPM Annual Meetings on the historical aspects of medical physics, radiology, and radiation oncology that have been organized by the AAPM History Committee. Information on previous presentations including “Early Developments in Teletherapy” (Indianapolis 2013), “Historical Aspects of Cross-Sectional Imaging” (Charlotte 2012), “Historical Aspects of Brachytherapy” (Vancouver 2011), “50 Years of Women in Medical Physics” (Houston 2008), and “Roentgen's Early Investigations” (Minneapolis 2007) can be found in the Education Section of the AAPM Website. The Austin 2014 History Symposium will be on “Evolution of Radiation Treatment Planning.” Overview - Radhe Mohan Treatment planning is one of the most critical components in the chain of radiation therapy of cancers. Treatment plans of today contain a wide variety of sophisticated information conveying the potential clinical effectiveness of the designed treatment to practitioners. Examples of such information include dose distributions superimposed on three- or even four-dimensional anatomic images; dose volume histograms, dose, dose-volume and dose-response indices for anatomic structures of interest; etc. These data are used for evaluating treatment plans and for making treatment decisions. The current state-of-the-art has evolved from the 1940s era when the dose to the tumor and normal tissues was estimated approximately by manual means. However, the symposium will cover the history of the field from the late-1950's, when computers were first introduced for treatment planning, to the present state involving the use of high performance computing and advanced multi-dimensional anatomic, functional and biological imaging, focusing only on external beam treatment planning. The symposium will start with a general overview of the treatment planning process including imaging, structure delineation, assignment of dose requirements, consideration of uncertainties, selection of beam configurations and shaping of beams, and calculations, optimization and evaluation of dose distributions. This will be followed by three presentations covering the evolution of treatment planning, which parallels the evolution of computers, availability of advanced volumetric imaging and the development of novel technologies such as dynamic multi-leaf collimators and online image guidance. This evolution will be divided over three distinct periods - prior to 1970's, the 2D era; from 1980 to the mid-1990's, the 3D era; and from the mid 1990's to today, the IMRT era. When the World was Flat: The Two-Dimensional Radiation Therapy Era” - Jacob Van Dyk In the 2D era, anatomy was defined with the aid of solder wires, special contouring devices and projection x-rays. Dose distributions were calculated manually from single field, flat surface isodoses on transparencies. Precalculated atlases of generic dose distributions were produced by the International Atomic Energy Agency. Massive time-shared main frames and mini-computers were used to compute doses at individual points or dose distributions in a single plane. Beam shapes were generally rectangular, with wedges, missing tissue compensators and occasional blocks to shield critical structures. Dose calculations were measurement-based or they used primary and scatter calculations based on scatter-air ratio methodologies. Dose distributions were displayed on line printers as alpha-numeric character maps or isodose patterns made with pen plotters. More than Pretty Pictures: 3D Treatment Planning and Conformal Therapy - Benedick A. Fraass The introduction of computed tomography allowed the delineation of anatomy three-dimensionally and, supported partly by contracts from the National Cancer Institute, made possible the introduction and clinical use of 3D treatment planning, leading to development and use of 3D conformal therapy in the 1980's. 3D computer graphics and 3D anatomical structure definitions made possible Beam's Eye View (BEV) displays, making conformal beam shaping and much more sophisticated beam arrangements possible. These conformal plans significantly improved target dose coverage as well as normal tissue sparing. The use of dose volume histograms, gross/clinical/planning target volumes, MRI and PET imaging, multileaf collimators, and computer-controlled treatment delivery made sophisticated planning approaches practical. The significant improvements in dose distributions and analysis achievable with 3D conformal therapy made possible formal dose escalation and normal tissue tolerance clinical studies that set new and improved expectations for improved local control and decreasing complications in many clinical sites. From the Art to the State of the Art: Inverse Planning and IMRT - Thomas R. Bortfeld While the potential of intensity modulation was recognized in the mid- 1980's, intensity-modulated radiotherapy (IMRT) did not become a reality until the mid-1990's. Broad beams of photons could be sub-divided into narrow beamlets whose intensities could be determined using sophisticated optimization algorithms to appropriately balance tumor dose with normal tissue sparing. The development of dynamic multi-leaf collimators (on conventional linear accelerators as well as in helical delivery devices) enabled the efficient delivery of IMRT. The evolution of IMRT planning is continuing in the form of Volumetric Modulated Arc Therapy (VMAT) and through advanced optimization tools, such as multi-criteria optimization, automated IMRT planning, and robust optimization to protect dose distributions against uncertainties. IMRT also facilitates “dose painting” in which different sub-volumes of the target are prescribed different doses. Clearly, these advancements are being made possible by the increasing power and lower cost of computers and developments in other fields such as imaging and operations research. Summary - Radhe Mohan The history does not end here. The advancement of treatment planning is expected to continue, leading to further automation and improvements in conformality and robustness of dose distributions, particularly in the area of particle therapy. Radiobiological modeling will gain emphasis as part of the planning process. Learning Objectives: The scope of changes in technology and the capabilities of radiation treatment planning The impact of these changes in the quality of treatment plans and optimality of dose distributions The impact of development in other fields (imaging, computers, operations research, etc.) on the evolution of radiation treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

From boundary data to bound states. Part II. Scattering angle to dynamical invariants (with twist)

We recently introduced in [9] a boundary-to-bound dictionary between gravitational scattering data and observables for bound states of non-spinning bodies. In this paper, we elaborate further on this holographic map. We start by deriving the following — remarkably simple — formula relating the periastron advance to the scattering angle: $ΔΦ(J,ε)=χ(J,ε)+χ(-J,ε)$, via analytic continuation in angular momentum and binding energy. Using explicit expressions from [9], we confirm its validity to all orders in the Post-Minkowskian (PM) expansion. Furthermore, we reconstruct the radial action for the bound state directly from the knowledge of the scattering angle. The radial action enables us to write compact expressions for dynamical invariants in terms of the deflection angle to all PM orders, which can also be written as a function of the PM-expanded amplitude. As an example, we reproduce our result in [9] for the periastron advance, and compute the radial and azimuthal frequencies and redshift variable to two-loops. Agreement is found in the overlap between PM and Post-Newtonian (PN) schemes. Last but not least, we initiate the study of our dictionary including spin. We demonstrate that the same relation between deflection angle and periastron advance applies for aligned-spin contributions, with J the (canonical) total angular momentum. Explicit checks are performed to display perfect agreement using state-of-the-art PN results in the literature. Using the map between test- and two-body dynamics, we also compute the periastron advance up to quadratic order in spin, to one-loop and to all orders in velocity. We conclude with a discussion on the generalized ‘impetus formula’ for spinning bodies and black holes as ‘elementary particles’. Our findings here and in [9] imply that the deflection angle already encodes vast amount of physical information for bound orbits, encouraging independent derivations using numerical and/or self-force methodologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Developing Open-Source Tools for Increasing the Efficiency of Synthetic Aviation Turbine Fuel Certification Process

FuelLib is an open-source Python-based fuel library, developed by NREL, that leverages the group contribution method (GCM) of [1] to systematically estimate the thermodynamic and transport properties of hydrocarbon fuels. FuelLib predicts these properties based on the molecular structure of individual compounds or compound families, using weight percentages of a fuel's composition, typically measured using techniques such as gas chromatography (GC). FuelLib enables property estimation over a wide range of temperatures and pressures of multi-component fuels in the absence of detailed molecular composition data, making it particularly valuable for complex fuel mixtures where detailed experimental characterization of fuel composition is unavailable. These capabilities contribute directly to synthetic aviation turbine fuels (SATF) development, supporting the short-term American Society for Testing and Materials (ASTM) qualification of drop-in fuels while potentially expanding ASTM boundaries to certify a broader range of fuels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

A fission matrix based validation protocol for computed power distributions in the advanced test reactor

The Idaho National Laboratory (INL) has been engaged in a significant multi year effort to modernize the computational reactor physics tools and validation procedures used to support operations of the Advanced Test Reactor (ATR) and its companion critical facility (ATRC). Several new protocols for validation of computed neutron flux distributions and spectra as well as for validation of computed fission power distributions, based on new experiments and well-recognized least-squares statistical analysis techniques, have been under development. In the case of power distributions, estimates of the a priori ATR-specific fuel element-to-element fission power correlation and covariance matrices are required for validation analysis. A practical method for generating these matrices using the element-to-element fission matrix is presented, along with a high-order scheme for estimating the underlying fission matrix itself. The proposed methodology is illustrated using the MCNP5 neutron transport code for the required neutronics calculations. The general approach is readily adaptable for implementation using any multidimensional stochastic or deterministic transport code that offers the required level of spatial, angular, and energy resolution in the computed solution for the neutron flux and fission source. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Recent advances in the Mercury Monte Carlo particle transport code

We review recent physics and computational science advances in the Mercury Monte Carlo particle transport code under development at Lawrence Livermore National Laboratory. We describe recent efforts to enable a nuclear resonance fluorescence capability in the Mercury photon transport. We also describe recent work to implement a probability of extinction capability into Mercury. We review the results of current parallel scaling and threading efforts that enable the code to run on millions of MPI processes. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗
DOE OSTI2020

Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow

In this work, we investigated stochastic distribution control theory-based traffic signal optimization to achieve a smooth and uniform flow of vehicles through signalized intersections. In this context, the static and linear dynamic stochastic distribution models were developed to express the relationship between the signal timing and the traffic queue length together with its probability density function. Two stochastic distribution control algorithms were designed to control the signal timing at intersections such that the probability density function of the traffic queue of each intersection road segment is made as narrow and as small as possible. Also, a recursive input-output traffic queue estimation model was proposed, which is data-driven and dynamic in nature, to calculate real-time traffic queue length using traffic signal timings and loop-detector data. The control algorithms were evaluated for a one-signal corridor, two-signal corridor, and 2 x 2 network of signalized intersections. MATLAB simulation examples are provided to demonstrate the use of the proposed algorithms and comparison to the existing widely-used semi-actuated control has been made. Desired results were obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

The art and power of data imaging

Data imaging and visual data assessment are veritable gold mines in the scientist's quest to understand and accurately interpret numerical data. Graphical displays of various aspects of a dataset offer the analyst insight to the data that no mathematical computation or statistic can provide. It is difficult, at best, for even a skilled and observant statistician to understand the underlying structure of a dataset. Often, there is either too little data to get a good 'picture' of the structure that might be present or there is so much data that one cannot readily assimilate it. Of course, the latter problem (too much data) is, in reality, no problem at all given the abilities of modern computers and software systems to manage large amounts of data. Advances in computer technology and the advent of the global positioning satellite system have enabled scientists from many fields of endeavor to collect and view data in its spatial context. Visual images constructed from spatially referenced data reveal the inherent richness and structure in the data and lead to more informed conclusions. So powerful is data collected with spatial context that a relatively new branch of mathematical statistics, geo-spatial statistics, has emerged. Geo-spatial statistics seek to exploit this context rich data form to better understand the spatial and co-relationships that might exist, but would be otherwise hidden in tabular data or obscured with classic statistical approaches. This paper (and accompanying presentation) will show the power that visual data assessment possesses to understand radiological scanning data and to make confident and accurate decisions based on the data images. It will challenge the traditional mathematical concept of detection limits for scanning. It will demonstrate that more data, even if the individual datum comprising the dataset is of 'poorer quality' (i.e., has a larger uncertainty and, thus, a larger calculated minimum detection value), is significantly more powerful than a smaller dataset comprised of higher quality measurements. This presentation will cause the open-minded health physicist to rethink how they prescribe, collect, evaluate, and make decisions based upon radiological scan data. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Virtualized Network Control. Final Report

This document is the final report for the Virtualized Network Control (VNC) project, which was funded by the United States Department of Energy (DOE) Office of Science. This project was also informally referred to as Advanced Resource Computation for Hybrid Service and TOpology NEtworks (ARCHSTONE). This report provides a summary of the project's activities, tasks, deliverable, and accomplishments. It also provides a summary of the documents, software, and presentations generated as part of this projects activities. Namely, the Appendix contains an archive of the deliverables, documents, and presentations generated a part of this project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Integrated Computational Materials Engineering Development of Advanced High Strength Steel for Lightweight Vehicles

The goal of the ICME 3GAHSS project was to successfully demonstrate the applicability of Integrated Computational Materials Engineering (ICME) for the development and deployment of third generation advanced high strength steels (3GAHSS) for immediate weight reduction in passenger vehicles. The ICME approach integrated results from well-established computational and experimental methodologies to develop a suite of material constitutive models (deformation and failure), manufacturing process and performance simulation modules, a properties database, as well as the computational environment linking them together for both performance prediction and material optimization. This is the Final Report for the ICME 3GAHSS project, which achieved the fol-lowing objectives: 1) Developed a 3GAHSS ICME model, which includes atomistic, crystal plasticity, state variable and forming models. The 3GAHSS model was implemented in commercially available LS-DYNA and a user guide was developed to facilitate use of the model. 2) Developed and produced two 3GAHSS alloys using two different chemistries and manufacturing processes, for use in calibrating and validating the 3GAHSS ICME Model. 3) Optimized the design of an automotive subassembly by substituting 3GAHSS for AHSS yielding a design that met or exceeded all baseline performance requirements with a 30% mass savings. A technical cost model was also developed to estimate the cost per pound of weight saved when substituting 3GAHSS for AHSS. The project demonstrated the potential for 3GAHSS to achieve up to 30% weight savings in an automotive structure at a cost penalty of up to $0.32 to $1.26 per pound of weight saved. The 3GAHSS ICME Model enables the user to design 3GAHSS to desired mechanical properties in terms of strength and ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Web-Based Computational Model Builder For Nuclear Energy Advanced Modeling and Simulation (Final Report)

According to the World Nuclear Association, the U.S. is the largest producer of nuclear power worldwide. In fact, the U.S. provides over 30 percent of the world's nuclear generation of electricity. Although few new reactors have been built in the past 30 years, the association anticipates that four to six reactors may be built by 2020. The first of the reactors will be built in response to 16 license applications, which have been completed since 2007, to build 24 additional nuclear reactors. Currently, both government and industry are working to accelerate approval for the construction and design of new nuclear energy plants. The U.S. nuclear industry has already achieved significant developments in the implementation of nuclear power plants due to advancements in refueling, maintenance, and safety systems at current power plants. Meanwhile, changes in government policy, which have occurred since the late 1990s, have provided for noteworthy expansion in nuclear capacity. For example, the Energy Policy Act of 2005 evoked investment in electricity infrastructure such as nuclear power. To design future systems and continue operational improvements at existing U.S. plants, advanced modeling and simulation of nuclear reactors are crucial. We developed a Cloud/Web-based tool, HPCCloud, that enables nuclear energy firms, or other manufacturing and engineering companies, to innovate using advanced modeling and simulation. Through the Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling and Simulation grant, we develop HPCCloud to simplify and democratize advanced modeling and simulation in the nuclear energy industry on a range of nuclear engineering applications. It leverages millions of investment dollars from the Department of Energy's Consortium for Advanced Simulation of Light Water Reactors (CASL) and the Office of Nuclear Energy's research and development in Nuclear Energy Advanced Modeling and Simulation (NEAMS). Our approach simplifies the workflow, alleviates the need for in-house computational science and engineering experts, and lowers the capital investments required for advanced modeling and simulation. The Cloud/Web-based simulation environment guides end-users and developers through the advanced modeling and simulation lifecycle. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where one can save, share, and even publish the full path of data from input to final analyzed results. HPCCloud addresses identified challenges to the nuclear energy industry's use of advanced modeling and simulation. With this unique Cloud/Web-based environment, we enable an ecosystem of synergistic activities, fueling new research and development for nuclear energy. HPCCloud lays the groundwork for commercialization, through customization, technology integration, and advanced research and development services.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Implementation of a Bayesian Engine for Uncertainty Analysis

In probabilistic risk assessment, it is important to have an environment where analysts have access to a shared and secured high performance computing and a statistical analysis tool package. As part of the advanced small modular reactor probabilistic risk analysis framework implementation, we have identified the need for advanced Bayesian computations. However, in order to make this technology available to non-specialists, there is also a need of a simplified tool that allows users to author models and evaluate them within this framework. As a proof-of-concept, we have implemented an advanced open source Bayesian inference tool, OpenBUGS, within the browser-based cloud risk analysis framework that is under development at the Idaho National Laboratory. This development, the “OpenBUGS Scripter” has been implemented as a client side, visual web-based and integrated development environment for creating OpenBUGS language scripts. It depends on the shared server environment to execute the generated scripts and to transmit results back to the user. The visual models are in the form of linked diagrams, from which we automatically create the applicable OpenBUGS script that matches the diagram. These diagrams can be saved locally or stored on the server environment to be shared with other users.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Envisioning Science in 2050

To explore future-focused questions that could impact the future of DOE, a Community of Interest (COI) on Future Scientific Methodologies, sponsored by the Office of Advanced Scientific Computing Research (ASCR), was held over three non-consecutive days in November 2020. The COI’s charge was to create a vision for how future computational fabrics might shape, and be shaped by, scientific and technological advances over the next 10 to 30 years.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Modeling Fluid Flow in Domains Containing Moving Interfaces

Numerical simulations of fluid flow in domains containing moving rigid objects or boundaries are still challenging when meshes have to be adapted and periodically regenerated. A numerical strategy that falls into the general category of Arbitrary Lagrangian - Eulerian (ALE) methods is being developed. The method is based on a fixed mesh that is locally modified both in space and time to describe the moving interfaces which are allowed to move independently of the mesh. This results in a fully robust formulation capable of calculating in irregular meshes containing moving devises of complex geometry and free of mesh entanglement problems. The present work constitutes the first stage in the development of a three-dimensional model to interface with the new KIVA-hpFE simulator. The method’s accuracy has been assessed in two dimensions using a case that has an analytical solution.

02 PETROLEUM↗