TECHNIQUES USED IN SHIELDING CALCULATIONS FOR HIGH-ENERGY ACCELERATORS- APPLICATIONS TO SPACE SHIELDING
Shielding methods for high-energy accelerators applied to spacecraft shielding
SPACECRAFT SHIELDING↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Accelerating the solution of the S N equations with highly anisotropic scattering using the Fokker-Planck approximation
The discrete ordinates method can model forward-peaked transport problems accurately. However, convergence of discrete ordinates solution can become arbitrarily slow upon use of standard iterative procedures like source iteration. Standard zeroth and first moment-based acceleration methods like nonlinear diffusion acceleration and diffusion synthetic acceleration are ineffective in accelerating such problems because these methods do not correct higher order Legendre-moments of angular flux. In this paper, we explore the idea of using the Fokker-Planck approximation as a preconditioner to accelerate the convergence of solution of forward-peaked transport problems. Finally, we observe that such preconditioning can successfully reduce the iteration count by up to four orders of magnitude, and solver runtime by up to three orders of magnitude when compared to diffusion synthetic acceleration.
42 ENGINEERING↗
Convergence acceleration of the Proteus computer code with multigrid methods
Presented here is the first part of a study to implement convergence acceleration techniques based on the multigrid concept in the Proteus computer code. A review is given of previous studies on the implementation of multigrid methods in computer codes for compressible flow analysis. Also presented is a detailed stability analysis of upwind and central-difference based numerical schemes for solving the Euler and Navier-Stokes equations. Results are given of a convergence study of the Proteus code on computational grids of different sizes. The results presented here form the foundation for the implementation of multigrid methods in the Proteus code.
Demuren, A. O.↗
Dynamic systems modeling of the spallation neutron source cryogenic moderator system to optimize transient control and prepare for power upgrades
Through support of the US Department of Energy's Office of Basic Energy Sciences, Oak Ridge National Laboratory has begun applying machine learning methods to improve accelerator and target performance of the Spallation Neutron Source (SNS). These methods are being applied to the control optimization and power upgrade of the SNS Cryogenic Moderator System (CMS). A numerical model of the CMS has been developed to study these optimizations and system modifications using EcosimPro. This paper compares steady-state and transient numerical results with experimental data. Control optimization studies focused on dampening mass flow, temperature, and pressure fluctuations during sudden losses of accelerator beam power. This analysis was conducted by adjusting five proportional-integral-derivative controllers connected to four flow control valves and one heater. Future efforts include power uprate studies focused on increasing the CMS cooling capacity. The current accelerator power is 1.4 MW; the first target station is being upgraded to 2.0 MW as part of the Proton Power Upgrade effort. The CMS cooling capacity is sufficient for 2.0 MW operation.
47 OTHER INSTRUMENTATION↗
Accelerating scientific discoveries through data-driven innovations
Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.
97 MATHEMATICS AND COMPUTING↗
Mitigation of Beam Losses in LANSCE Linear Accelerator
Suppression of beam losses is essential for successful operation of high-intensity accelerator facility. The LANSCE accelerator started routine operation in 1972 as a 0.8 MW average proton beam power facility for meson physics research, and delivered highpower beam for a quarter century. The accelerator currently delivers 100 MeV proton beam to Isotope Production Facility (IPF) and 800 MeV H- beams to various experimental areas. The accelerator is equipped with two independent injectors for H + and H - beams, merging at the entrance of a 201.25 MHz Drift Tube Linac (DTL). The DTL performs acceleration up to the energy of 100 MeV. After the DTL, the Transition Region beamline directs a 100 MeV proton beam to the Isotope Production Facility, while the H - beam is accelerated up to the final energy of 800 MeV in an 805- MHz Coupled Cavity Linac. The H - beams, created with different time structure by a lowenergy chopper, are distributed in the Switch Yard (SY) to four experimental areas: the Lujan Neutron Scattering Center equipped with a Proton Storage Ring (PSR), the Weapons Neutron Research facility (WNR), the Proton Radiography facility (pRad), and the Ultra-Cold Neutron facility (UCN). Multi-beam operation requires careful control of accelerator tune to minimize beam losses. In this paper we review main effects affecting beam losses in LANSCE linear accelerator and discuss methods to reduce them.
43 PARTICLE ACCELERATORS↗
Laser interferometry method for absolute measurement of the acceleration of gravity
Gravimeter permits more accurate and precise absolute measurement of g without reference to Potsdam values as absolute standards. Device is basically Michelson laser beam interferometer in which one arm is mass fitted with corner cube reflector.
Hudson, O. K.↗
System and method for alfvenic reconnecting plasmoid plasma acceleration
According to various embodiments, a system for using magnetic reconnection to accelerate plasma is disclosed. The system includes a pair of electrodes including two concentric rings separated by an electrode gap and held at different electrostatic potential by applying a voltage to generate an inter-electrode electric field. The system further includes a plurality of magnetic coils configured to produce magnetic field lines that connect the pair of electrodes. The system additionally includes a gas injector configured to inject gas into the electrode gap, the injected gas being partially ionized by the inter-electrode electric field to generate a poloidal current that flows along open magnetic field lines across the electrode gap. A total Lorentz force causes oppositely directed magnetic field lines to be expanded around a region of the gas injector to further create an azimuthal current in the form of an axially elongated current sheet that is unstable such that the axially elongated current sheet reconnects and breaks into plasmoids.
Ebrahimi, Fatima Arezu↗
Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems
This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.
Visweswara Sathanur, Arun↗
Examination of Ac-225 production from Ra-226 using fast reactor JOYO
In this study, the authors investigated the method of producing the radionuclide Ac{sup 225} used for targeted alpha therapy (TAT). Currently, Ac{sup 225} is mainly generated from ORNL's Th{sup 229} generator, and the annual production amount is limited to about 63 GBq, and methods for generating it using accelerators are under development in each country. The method using an accelerator has the advantage of being able to generate Ac{sup 225} from a small amount of target nuclides with high efficiency but has the disadvantage of not being able to irradiate a large amount of target nuclides at once due to the small irradiation area. Therefore, the authors investigated a method to generate Ac{sup 225} by neutron irradiation of Ra{sup 226} as a target nuclide using the experimental fast reactor JOYO, which has abundant neutrons and a large loading region. Irradiation of Ra{sup 226} with fast neutrons causes a (n, 2n) reaction to generate Ra{sup 225}, and then decay to produce Ac{sup 225}. In addition, although harmful Ac{sup 227} is also produced at the same time by the (n,γ) reaction, first of all the actinium isotope is chemically separated and eliminated. Since the remaining Ra{sup 225} collapses and Ac{sup 225} is produced, pure Ac{sup 225} can be extracted by performing chemical separation again. As a result of the analysis, 1 g of Ra{sup 226} is irradiated with JOYO for 60 days, and milking is performed 4 times every 17.5 days. By doing these three times a year, it was found that about 50 GBq of Ac{sup 225} was generated. (authors)
07 ISOTOPE AND RADIATION SOURCES↗
The block adaptive multigrid method applied to the solution of the Euler equations
In the present study, a scheme capable of solving very fast and robust complex nonlinear systems of equations is presented. The Block Adaptive Multigrid (BAM) solution method offers multigrid acceleration and adaptive grid refinement based on the prediction of the solution error. The proposed solution method was used with an implicit upwind Euler solver for the solution of complex transonic flows around airfoils. Very fast results were obtained (18-fold acceleration of the solution) using one fourth of the volumes of a global grid with the same solution accuracy for two test cases.
Pantelelis, Nikos↗
General image method in a plane-layered elastostatic medium
The general-image method presently used to obtain the elastostatic fields in plane-layered media relies on the use of potentials in order to represent elastic fields. For the case of a single interface, this method yields the displacement field in closed form, and is applicable to antiplane, plane, and three-dimensional problems. In the case of multiplane interfaces, the image method generates the displacement fields in terms of infinite series whose convergences can be accelerated to improve method efficiency.
Fares, N.↗
Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications
Artificial intelligence (AI) promises powerful new capabilities in an expansive array of applications. One area is proliferation detection, where AI can provide transformative tools to achieve objectives currently inaccessible using conventional methods. In particular, AI affords the opportunity to use new indicators and process massive amounts of heterogeneous data that can increase sensitivity to proliferant activities and push proliferation detection to the earliest possible stages. However, existing AI tools are not ready to achieve such potential, falling short in regard to some important considerations involved in proliferation detection. One crucial aspect that requires improvement is the explainability of the most powerful AI algorithms (i.e., understanding how the algorithms actually arrive at their conclusions)-the lack of which prevents widespread adoption in national security missions. The Data Science and AI portfolio within the National Nuclear Security Administration's Office of Defense Nuclear Nonproliferation Research and Development is driving the development of next-generation AI for proliferation detection through the expertise and work of the national laboratories and partners in academia. The "Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications" workshop aimed to further this objective. The meeting was held virtually on Sept. 15-16, 2020 and included more than 170 participants, primarily from the national laboratories with additional contributions from university researchers and mission partners. Each day included a keynote presentation, four technical presentations about cutting-edge research in explainability, and a panel to explore considerations in applying explainability and developing AI systems that can accelerate the transition of emerging AI technologies among partners and end users to solve critical mission questions. This report summarizes the Next-Gen AI for Proliferation Detection workshop's content and findings.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Linear stability analysis via simulated annealing and accelerated relaxation
Simulated annealing (SA) is a kind of relaxation method for finding equilibria of Hamiltonian systems. A set of evolution equations is solved with SA, which is derived from the original Hamiltonian system so that the energy of the system changes monotonically while preserving Casimir invariants inherent to noncanonical Hamiltonian systems. The energy extremum reached by SA is an equilibrium. Since SA searches for an energy extremum, it can also be used for stability analysis when initiated from a state where a perturbation is added to an equilibrium. The procedure of the stability analysis is explained, and some examples are shown. Because the time evolution is computationally time consuming, efficient relaxation is necessary for SA to be practically useful. An acceleration method is developed by introducing time dependence in the symmetric kernel used in the double bracket, which is part of the SA formulation described here. An explicit formulation for low-beta reduced magnetohydrodynamics (MHD) in cylindrical geometry is presented. In conclusion, since SA for low-beta reduced MHD has two advection fields that relax, it is important to balance the orders of magnitude of these advection fields.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
RNS Applications for Interacting Sub- and Supersonic Flows
A solution based grid adaptation method that combines elements of the multigrid method for solution acceleration and the domain decomposition philosophy for grid optimization is described. Unlike other solution based adaptive gridding schemes, wherein the overhead of recomputing the grid and re-evaluating the solution on the adapted grid leads to higher computational costs compared to a non-adapted calculation, the present methodology reduces the computational time required to obtain the solution. The computational effort involved in the present calculation is significantly lower than a non-adapted calculation that utilizes the multigrid method purely as a convergence acceleration tool. In addition to convergence acceleration, the multigrid framework provides a mechanism of information transfer from regions wherein grid refinement is specified to unrefined coarse grid regions. The basis for domain decomposition in the current procedure is the variation in grid refinement requirements for each coordinate direction in different portions of the flow field. The method is demonstrated herein on an efficient set of governing equations termed the reduced Navier Stokes equations, applied in conjunction with a set of physical boundary conditions. The governing equations are discretized through a pressure based flux splitting procedure that is uniformly applicable from incompressible to supersonic Mach numbers.
Rubin, Stanley G.↗
One shot methods for optimal control of distributed parameter systems 1: Finite dimensional control
The efficient numerical treatment of optimal control problems governed by elliptic partial differential equations (PDEs) and systems of elliptic PDEs, where the control is finite dimensional is discussed. Distributed control as well as boundary control cases are discussed. The main characteristic of the new methods is that they are designed to solve the full optimization problem directly, rather than accelerating a descent method by an efficient multigrid solver for the equations involved. The methods use the adjoint state in order to achieve efficient smoother and a robust coarsening strategy. The main idea is the treatment of the control variables on appropriate scales, i.e., control variables that correspond to smooth functions are solved for on coarse grids depending on the smoothness of these functions. Solution of the control problems is achieved with the cost of solving the constraint equations about two to three times (by a multigrid solver). Numerical examples demonstrate the effectiveness of the method proposed in distributed control case, pointwise control and boundary control problems.
Taasan, Shlomo↗
Accelerated Materials Design for Molten Salt Technologies Using Innovative High-Throughput Methods
The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.
36 MATERIALS SCIENCE↗
Enabling More than Moore: Accelerated Reliability Testing and Risk Analysis for Advanced Electronics Packaging
For five decades, the semiconductor industry has distinguished itself by the rapid pace of improvement in miniaturization of electronics products-Moore's Law. Now, scaling hits a brick wall, a paradigm shift. The industry roadmaps recognized the scaling limitation and project that packaging technologies will meet further miniaturization needs or ak.a "More than Moore". This paper presents packaging technology trends and accelerated reliability testing methods currently being practiced. Then, it presents industry status on key advanced electronic packages, factors affecting accelerated solder joint reliability of area array packages, and IPC/JEDEC/Mil specifications for characterizations of assemblies under accelerated thermal and mechanical loading. Finally, it presents an examples demonstrating how Accelerated Testing and Analysis have been effectively employed in the development of complex spacecraft thereby reducing risk. Quantitative assessments necessarily involve the mathematics of probability and statistics. In addition, accelerated tests need to be designed which consider the desired risk posture and schedule for particular project. Such assessments relieve risks without imposing additional costs. and constraints that are not value added for a particular mission. Furthermore, in the course of development of complex systems, variances and defects will inevitably present themselves and require a decision concerning their disposition, necessitating quantitative assessments. In summary, this paper presents a comprehensive view point, from technology to systems, including the benefits and impact of accelerated testing in offsetting risk.
Ghaffarian, Reza↗