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At least 1,369 records · Page 76

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DOE OSTI2019

Advances in global optimization of high brightness beams

High brightness electron beams play an important role in accelerator-based applications such as driving X-ray free electron laser (FEL) radiation.Here in this paper, we report on advances in global beam dynamics optimization of an accelerator design using start-to-end simulations and a new parallel multi-objective differential evolution optimization method. The global optimization results in significant improvement of the final electron beam brightness.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗

DOE OSTI2019

Exploring Acceleration Schemes for Nonlinear Heat Equations in Fusion Reactor Modeling

Plasma modeling inside a tokamak reactor poses a challenging and often times computationally expensive endeavor. The process of running these simulations has the potential to increase the predictive capabilities of these models. Here we investigate the effect particular acceleration schemes, mainly Anderson Acceleration, have on a nonlinear transport equation solver, Tango, developed by Parker et al. We show that Anderson acceleration offers a method for decreasing the computational cost through a test problem developed by Shestakov et al, which shows promise towards utilizing Anderson Acceleration in complex transport simulations

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Bayesian optimization algorithms for accelerator physics

Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design and model calibration in simulations. The effectiveness of optimization algorithms in discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. The accelerator physics community has recognized the advantages of Bayesian optimization algorithms, which leverage statistical surrogate models of objective functions to effectively address complex optimization challenges, especially in the presence of noise during accelerator operation and in resource-intensive physics simulations. In this review article, we offer a conceptual overview of applying Bayesian optimization techniques toward solving optimization problems in accelerator physics. We begin by providing a straightforward explanation of the essential components that make up Bayesian optimization techniques. We then give an overview of current and previous work applying and modifying these techniques to solve accelerator physics challenges. Finally, we explore practical implementation strategies for Bayesian optimization algorithms to maximize their performance, enabling users to effectively address complex optimization challenges in real-time beam control and accelerator design. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

GPU-accelerated dislocation dynamics using subcycling time-integration

Discrete dislocation dynamics (DDD) simulations are being increasingly employed to investigate metal plasticity at the mesoscale. However, in spite of its ability to access beyond the length and time limits of atomistic methods, the DDD model is still limited by its high computational cost, with ranges of achievable strains too low and strain rates too high by several orders of magnitude compared with typical experimental conditions. By combining the efficiency of the recently developed subcycling time-integrator with the highly parallel architecture of graphics processing unit (GPU) devices, we developed a DDD model that provides significant acceleration compared to existing implementations. Our GPU-accelerated implementation enables large-scale DDD simulations that can reach relevant levels of strain using a moderate amount of computational resources.

36 MATERIALS SCIENCE↗

DOE OSTI2014

SEP acceleration in CME driven shocks using a hybrid code

We perform hybrid simulations of a super-Alfvénic quasi-parallel shock, driven by a coronal mass ejection (CME), propagating in the outer coronal/solar wind at distances of between 3 to 6 solar radii. The hybrid treatment of the problem enables the study of the shock propagation on the ion timescale, preserving ion kinetics and allowing for a self-consistent treatment of the shock propagation and particle acceleration. The CME plasma drags the embedded magnetic field lines stretching from the sun, and propagates out into interplanetary space at a greater velocity than the in situ solar wind, driving the shock, and producing very energetic particles. Our results show that electromagnetic Alfvén waves are generated at the shock front. The waves propagate upstream of the shock and are produced by the counter-streaming ions of the solar wind plasma being reflected at the shock. A significant fraction of the particles are accelerated in two distinct phases: first, particles drift from the shock and are accelerated in the upstream region, and second, particles arriving at the shock get trapped and are accelerated at the shock front. A fraction of the particles diffused back to the shock, which is consistent with the Fermi acceleration mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Large-scale simulations require efficient computation across the entire computing hierarchy. A challenge of the Exascale Computing Project (ECP) was to reconcile highly heterogeneous hardware with the myriad of applications that were required to run on these supercomputers. Mathematical software forms the backbone of almost all scientific applications, providing efficient abstractions and operations that are crucial to harness the performance of computing systems. Ginkgo is one such mathematical software library, nurtured by ECP, providing high-performance, user-friendly, and performance portable interfaces for applications in ECP and beyond. In this paper, we elaborate on Ginkgo’s philosophy of high-performance software that is sustainable, reproducible, and easy to use. We showcase the wide feature set of solvers and preconditioners available in Ginkgo and the central concepts involved in their design. We elaborate on four different ECP software integrations: MFEM, PeleLM + SUNDIALS, XGC, and ExaSGD that use Ginkgo to accelerate their science runs. Performance studies of different problems from these applications highlight the effectiveness of Ginkgo and the benefits incurred by these ECP applications.

Cojean, Terry↗

DOE OSTI2022

X-ray FEL linear accelerator design via start-to-end global optimization

An X-ray Free Electron Laser (FEL) prefers using an electron beam with low emittance, small energy spread, and a high core current to generate coherent radiation through an undulator. In order to attain such a high brightness beam, the linear accelerator beam dynamics design generally involves separate photoinjector optimization and linac optimization. In this paper, we propose a new beam dynamics design strategy based on global optimization with fast start-to-end simulations from the photocathode to the end of the accelerator. The new start-to-end model significantly reduces the simulation time and makes the global optimization practical. The global optimization method avoids the need to choose a single solution based on bunch length at the injector exit for the linac optimization and helps find the solution with unfavorable bunch length at the injector exit but better phase space distribution that can result in better final electron beam phase space distribution at the entrance of the undulator. Here, using the start-to-end global optimization, we showed in an application example, with a 100 pC beam that good transverse emittance and over kilo-Ampere final core current can be attained using a photoinjector that consists of a VHF gun and boosting RF cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Simulation of incoherent ion effects in electron storage rings

Not Available

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Monte Carlo simulations of photoneutron activation in a medical LINAC

The first step of the present study was to simulate the γ-radioactivity produced by photoneutrons in the treatment head of a decommissioned medical LINAC. These results, obtained with MCNPX and CINDER'90, are then compared with γ-ray spectrometric measurements of parts of the treatment head. Our ultimate objective is to simulate the associated production by photonuclear reactions of pure β-emitters, which are more difficult to access experimentally than the γ-ray emitters. (authors)

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

Acceleration of saddle-point searches with machine learning

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Laser vacuum acceleration of a relativistic electron bunch

With regard to the problem of laser acceleration of a relativistic electron bunch we present a scheme of its vacuum acceleration directly by a relativistic intensity laser pulse. The energy of the electron bunch injected into the laser pulse leading edge increases during its coaxial movement to a thin, pulse-reflecting target. The laser-accelerated electrons continue to move free forward, passing through the target. The study of this acceleration scheme in the three-dimensional geometry is verified in a numerical simulation by the particle-in-cell method, which showed that the energy of a part of the electrons can increase significantly compared to the initial one. Restrictions are discussed, which impose limiting values of energy and total charge of accelerated electrons. (superstrong light fields)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

On the possibility of generating low-energy positrons on accelerators of electrons with a beam energy of a few MeV and on terawatt lasers

Based on the numerical simulations, we estimate the possibility of generating positrons by low-energy electrons (below 10 MeV) produced by electron accelerators and femtosecond lasers. A review of experimental work reported in the literature is presented. The simulation is carried out using the GEANT-4 software package for the particular conditions of a possible experiment at the terawatt femtosecond laser facility of the International Laser Centre at the Moscow State University and the LUE-8 MeV linear electron accelerator at the Institute for Nuclear Research, Russian Academy of Sciences. (paper)

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

When and how to treat an IMRT patient on a second accelerator without replanning?

When a linear accelerator is unavailable for treatment, a clinical decision is imminent regarding whether a patient should be treated on a linear accelerator other than the machine the patient was scheduled on, or whether treatment should be postponed until the original Linac becomes available. This work investigates the feasibility of switching patients to different accelerators for intensity-modulated radiation therapy (IMRT). We have performed Monte Carlo simulations of photon beams from different Linac models and vendors. Prostate and head and neck (H&N) treatment plans for Siemens Primus, Primart, and Varian 21EX accelerators are studied in this work. Dose distributions for given plans are recalculated using different beam data with the same nominal energy from different Linacs. We have compared dose-volume histograms (DVHs) and the maximum, the minimum, and the mean doses to the target and critical structures because of switching accelerators. In the process of switching a treatment plan to a different accelerator, issues exist, including optimum penumbra compensation, dose distribution at the boundary of target and critical structures, and multileaf collimator (MLC) leaf-width effects, which need to be considered and verified with measurements. Our Monte Carlo simulation results confirm that, for the cases we tested, the dose received by 95% of the planning target volume differs by 0.2% to 1.5% between Siemens Primus and Varian 21EX Linacs. The discrepancy is within our clinical acceptance criteria of 3% for IMRT treatments. In making the final decision on whether to switch machines or not, the tumor control probabilities (TCPs) based on a linear-quadratic model are compared. Based on the analyses performed in this work, it is therapeutically more beneficial to switch a patient to a different machine than to postpone a treatment until the original machine is available, especially for fast-growing tumors such as H&N cancers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Simulation of Proton Beams in the AGS Booster with Space Charge

As higher intensity accelerators are designed, built and operated, the resonances and instabilities caused by space charge can become dominant effects in limiting the intensity of the beam that can be delivered. Particle loss has many causes but space charge can be a major factor in reducing beam intensity and generating emittance growth, particularly at low energies and in the lower energy stages of accelerators such as the AGS Booster. Successful operation relies on a good understanding of basic particle dynamics and it becomes an important challenge to ascertain how the beam evolves when charged particles experience both external forces through the fields of the magnets combined with internal forces through Coulomb interactions. A possible approach to such a study is to include calculations of space charge in computer simulation codes that track the motions of charged particles in 6D phase space. Unfortunately, repeated space charge calculations in 6D phase space are computationally intensive even with the most modern computing facilities. Study with traditional models of space charge is then either limited to a short real-time scale, or sacrifices accuracy and often omits some of the physics. The study described in this report attempts to explore all aspects of the Booster from injection, through RF capture and acceleration to the extraction energy. The simulations are allied to real machine settings. They do not attempt to model effects that are well known and for which accurate experimental data are available, but they try in many cases to extend beyond the normal Booster parameter range so as to understand the limitations on operations and suggest areas for improvement.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

On the Need for a Unified and Collaboratively Developed Residential Building Simulation Platform: Preprint

Residential building energy simulations are becoming ever more pervasive; they form the basis of energy efficient building design, zero energy goals, codes and standards, home certification and ratings industries, utility programs, regional/state planning, and technology assessments. And yet the residential building simulation community is highly fragmented with a patchwork of simulation engines with varying models, inputs, assumptions, and results. This inconsistency degrades confidence in these tools, increases industry-wide development and maintenance costs, and slows the availability of new efficiency technology models. The need for collaboration on an impartial, transparent, and capable residential building simulation platform has never been greater. But to develop and maintain a state-of-the-art simulation platform requires a dedicated and sustained investment. By leveraging existing resources and expertise from multiple entities/regions, a unified and collaboratively developed simulation platform can provide increased levels of energy efficiency at an accelerated pace. This paper presents the advantages and disadvantages of a unified residential building simulation platform in relationship to four real-world examples (RESNET HERS ratings, utility programs, California's Title 24, and DOE). The paper covers recent developments and improved capabilities that may move us closer to an ideal simulation platform and what challenges remain. The hope is to spur a frank and honest dialogue about how to work together towards the vision of achieving deeper and more reliable energy savings in the residential buildings industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

On the Need for a Unified and Collaboratively Developed Residential Building Simulation Platform

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors

Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗