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At least 1,243 records · Page 69

Vibrationally averaged dipole moments of methane and benzene isotopologues

DFT-B3LYP post-Born-Oppenheimer (finite-nuclear-mass-correction (FNMC)) calculations of vibrationally averaged isotopic dipole moments of methane and benzene, which compare well with experimental values, are reported. For methane, in addition to the principal vibrational contribution to the molecular asymmetry, FNMC accounts for the surprisingly large Born-Oppenheimer error of about 34% to the dipole moments. This unexpected result is explained in terms of concurrent electronic and vibrational contributions. The calculated dipole moment of C{sub 6}H{sub 3}D{sub 3} is about twice as large as the measured dipole moment of C{sub 6}H{sub 5}D. Computational progress is advanced concerning applications to larger systems and the choice of appropriate basis sets. The simpler procedure of performing vibrational averaging on the Born-Oppenheimer level and then adding the FNMC contribution evaluated at the equilibrium distance is shown to be appropriate. Also, the basis set choice is made by heuristic analysis of the physical behavior of the systems, instead of by comparison with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing Radiation Resistance in Materials for Fusion Energy

Proposed fusion and advanced (Generation IV) fission energy systems require high performance materials capable of satisfactory operation up to neutron damage levels approaching 200 atomic displacements per atom with large amounts of transmutant hydrogen and helium isotopes. After a brief overview of fusion reactor concepts and radiation effects phenomena in structural and functional (non-structural) materials, three fundamental options for designing radiation resistance are outlined: Utilize matrix phases with inherent radiation tolerance, select materials where vacancies are immobile at the design operating temperatures, or construct high densities of point defect recombination sinks. Environmental and safety considerations impose several additional restrictions on potential materials systems, but reduced activation ferritic/martensitic steels (including thermomechanically treated and oxide dispersion strengthened options) and silicon carbide ceramic composites emerge as robust structural materials options. Materials modeling (including computational thermodynamics) and advanced manufacturing methods are poised to exert a major impact in the next ten years.

Zinkle, Steven J↗

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗

An accelerated framework for predicting creep rupture lifetimes in engineering alloys

Confidently predicting high-temperature deformation, including creep and creep rupture, is paramount for the design and commercialization of candidate materials for advanced nuclear energy systems. To accelerate creep quantification, we introduce a framework that enables rapid, cost-effective, and reliable prediction of creep rupture lifetimes, minimizing reliance on time-intensive bulk creep testing. Unlike conventional creep analysis, which requires extensive time and resources, our method leverages a maximum of four short-term bulk creep tests as training data for prediction. This framework combines high-throughput nanoindentation up to 700 °C with these targeted bulk tests to inform our creep rupture model in order to predict rupture lifetimes. The strong agreement between our predictions and conventional experimental data demonstrates the effectiveness of our approach for accelerated creep analysis and lifetime prediction of structural components in high-temperature applications. Our multi-pronged approach motivates further integration of computational tools and advanced instrumentation to establish a universal framework for understanding high-temperature material responses.

36 MATERIALS SCIENCE↗

Splitting phonons: Building a platform for linear mechanical quantum computing

Linear optical quantum computing provides a desirable approach to quantum computing, with only a short list of required computational elements. The similarity between photons and phonons points to the interesting potential for linear mechanical quantum computing using phonons in place of photons. Although single-phonon sources and detectors have been demonstrated, a phononic beam splitter element remains an outstanding requirement. Here we demonstrate such an element, using two superconducting qubits to fully characterize a beam splitter with single phonons. We further use the beam splitter to demonstrate two-phonon interference, a requirement for two-qubit gates in linear computing. In conclusion, this advances a new solid-state system for implementing linear quantum computing, further providing straightforward conversion between itinerant phonons and superconducting qubits.

97 MATHEMATICS AND COMPUTING↗

C3PU:Real-Time Predictive Charge Control Software for Battery Management Systems (Code for Charge Control and Predictive Unit) [SWR-21-48]

C3PU sets up a model predictive control formulation for the optimal charging control of battery packs and can be deployed for real-time operation on an embedded microprocessor. C3PU uses electrochemical and thermal models of battery packs to predict the charging trajectories of the battery pack over a time horizon under different operating conditions. It then selects the optimal charging trajectory such that a pre-defined objective is minimized, which in the present state of the code is to minimize the charging duration of the battery pack. The optimal charging trajectory is obtained by solving an underlying mathematical problem. However, C3PU is flexible to incorporate other charging objectives. The underlying battery models can be swapped as well, as long as they follow certain mathematical properties. Mathematically, optimal control problems (in this case, optimally controlling the charging current of the battery pack) are computationally expensive. C3PU implements advanced numerical techniques, namely pseudo-spectral optimization, to reduce the computational burden of the underlying problem to solve. This allows for the problem to be solved in real-time in an embedded system. Once the optimal charging trajectory is computed over a time horizon, C3PU can package such data and send it out via appropriate communication protocols.

Mishra, Partha↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Equation of state of boron nitride combining computation, modeling, and experiment

The equation of state (EOS) of materials at warm dense conditions poses significant challenges to both theory and experiment. We report a combined computational, modeling, and experimental investigation leveraging new theoretical and experimental capabilities to investigate warm-dense boron nitride (BN). The simulation methodologies include path integral Monte Carlo (PIMC), several density functional theory (DFT) molecular dynamics methods [plane-wave pseudopotential, Fermi operator expansion (FOE), and spectral quadrature (SQ)], activity expansion (actex), and all-electron Green's function Korringa-Kohn-Rostoker (mecca), and compute the pressure and internal energy of BN over a broad range of densities and temperatures. Our experiments were conducted at the Omega laser facility and the Hugoniot response of BN to unprecedented pressures (1200–2650 GPa). The EOSs computed using different methods cross validate one another in the warm-dense matter regime, and the experimental Hugoniot data are in good agreement with our theoretical predictions. By comparing the EOS results from different methods, we assess that the largest discrepancies between theoretical predictions are ≲ 4% in pressure and ≲ 3% in energy and occur at 10 6 K, slightly below the peak compression that corresponds to the K -shell ionization regime. At these conditions, we find remarkable consistency between the EOS from DFT calculations performed on different platforms and using different exchange-correlation functionals and those from PIMC using free-particle nodes. This provides strong evidence for the accuracy of both PIMC and DFT in the high-pressure, high-temperature regime. Moreover, the recently developed SQ and FOE methods produce EOS data that have significantly smaller statistical error bars than PIMC, and so represent significant advances for efficient computation at high temperatures. The shock Hugoniot predicted by PIMC, actex, and mecca shows a maximum compression ratio of 4.55 ± 0.05 for an initial density of 2.26 g/cm 3 , higher than the Thomas-Fermi predictions by about 5%. In addition, we construct tabular EOS models that are consistent with the first-principles simulations and the experimental data. Our findings clarify the ionic and electronic structure of BN over a broad range of temperatures and densities and quantify their roles in the EOS and properties of this material. The tabular models may be utilized for future simulations of laser-driven experiments that include BN as a candidate ablator material.

36 MATERIALS SCIENCE↗

Variational Quantum Eigensolver of Interacting Bosons with NISQ Devices [Slides]

Interacting bosons attract broad interest from different fields of physics and is often challenging to simulate on a classical computer. The recent advances in variational-quantum-eigensolver (VQE) algorithms offer a new and scalable way to investigate these interacting boson systems with noisy intermediate scale quantum (NISQ) devices. In this work, we present a proof-of-principle experiment of a boson VQE algorithm implemented on Rigetti's 8Q-device. Our experiment determines the low-energy eigenspectrum of the Rabi model -- a simple boson model with interactions mediated by an atom. Our result illustrates the promising future of scalable quantum simulation of interacting bosons using NISQ devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code

This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Some specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000 ® problems. These benchmark and scaling studies show promising results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An efficient tensor transpose algorithm for multicore CPU, Intel Xeon Phi, and NVidia Tesla GPU

An efficient parallel tensor transpose algorithm is suggested for shared-memory computing units, namely, multicore CPU, Intel Xeon Phi, and NVidia GPU. The algorithm operates on dense tensors (multidimensional arrays) and is based on the optimization of cache utilization on x86 CPU and the use of shared memory on NVidia GPU. From the applied side, the ultimate goal is to minimize the overhead encountered in the transformation of tensor contractions into matrix multiplications in computer implementations of advanced methods of quantum many-body theory (e.g., in electronic structure theory and nuclear physics). A particular accent is made on higher-dimensional tensors that typically appear in the so-called multireference correlated methods of electronic structure theory. Depending on tensor dimensionality, the presented optimized algorithms can achieve an order of magnitude speedup on x86 CPUs and 2-3 times speedup on NVidia Tesla K20X GPU with respect to the na ve scattering algorithm (no memory access optimization). Furthermore, the tensor transpose routines developed in this work have been incorporated into a general-purpose tensor algebra library (TAL-SH).

97 MATHEMATICS AND COMPUTING↗

HPC Node Performance and Energy Modeling with the Co-Location of Applications

Multicore processors have become an integral part of modern large-scale and high-performance parallel and distributed computing systems. This advance became necessary as the demand for increased system performance has exceeded the limits that single core processors can provide. Unfortunately, applications co-located on multicore processors can suffer from decreased performance and increased dynamic energy use as a result of access to shared resources, such as memory. Consequently, it is increasingly important to characterize the performance of applications that execute on these architectures. This work investigates some of the disadvantages of co-location, and presents a methodology for building models capable of utilizing varying amounts of information about a target application and its co-located applications to make predictions about the target application’s execution time and the system’s energy use under arbitrary co-locations of a wide range of application types. The proposed methodology is validated on three different server class Intel Xeon multicore processors using eleven applications from two scientific benchmark suites. The model’s utility for scheduling is also demonstrated in a simulated large-scale high-performance computing environment through the creation of a co-location aware scheduling heuristic. This heuristic demonstrates that scheduling using information generated with the proposed modeling methodology is capable of making significant improvements over a scheduling heuristic that is naive to co-location interference.

performance modeling, energy modeling, resource ma↗

Status Report on Development of MARCH Module Designs

The Transient Reactor Test (TREAT) facility was constructed in the late 1950’s, provided thousands of transient irradiations before being placed in standby in 1994, and was restarted in 2017 in order to resume its crucial role in nuclear heated safety research. Advances in modern computational capabilities and a resurgence of interest in novel reactor technology have created an opportunity for emphasizing modern science-based and separate effects test capabilities at TREAT. An innovative approach to this type of testing leverages the relatively low radioisotope accumulation during brief TREAT irradiations by arranging small fresh fuel specimens in low activation hardware “modules” so that they can be easily extracted and shipped for examination within weeks. The concept was termed the Minimal Activation Retrievable Capsule Holder (MARCH) irradiation vehicle system, and its maturation began under a Lab Directed Research and Development (LDRD) project starting in fiscal year 2017. Within the first year of this project, enough design and predictive modeling had been performed to prove the principle and ascertain support from major direct-funded DOE fuel development programs including the Accident Tolerant Fuels (ATF) program that sponsored the first modern fueled test to be performed in TREAT using the MARCH system. Since the design was modular in nature, it was straightforward for other sources to adopt and mature viable test modules while the LDRD project continued concurrently for two more years in conceptualizing and demonstrating the viability of other innovative modules. Many of these modules were adopted for continued development and irradiation under the Advanced Fuels Campaign and other direct sources. This report summarizes the MARCH modules that were conceptualized, designed, and deployed to date with the primary aim of providing reference information to future experiment designers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of Irradiation Test Devices for Transient Testing

The Transient Reactor Test facility (TREAT) resumed operations in 2017 in order to reclaim its crucial role in nuclear-heated fuel safety research. TREAT’s historic era of operation (1959-1994) was best known for integral-scale testing of large fuel specimens/bundles under postulated reactor plant accident conditions, but TREAT also supported smaller-scale phenomena identification tests that elucidated fundamental behaviors and paved the way for these integral-scale tests. Advances in modern computational capabilities and a resurgence of interest in novel reactor technologies have created an opportunity for emphasizing modernized science-based and separate effects tests once again at TREAT. An innovative approach to this type of testing has been developed to leverage minor radioactivity built-in during brief TREAT irradiations by arranging smaller fuel specimens in low activation hardware so that they can be easily extracted and shipped for post irradiation examination within weeks. This recently-established capability, termed the Minimal Activation Retrievable Capsule Holder (MARCH) irradiation vehicle system, includes capabilities for cost-effective simplified-environment testing of centimeter-scale fuel samples of various geometries, temperature-controlled irradiations of millimeter-size samples for lower-length-scale model development, liquid-metal bonded heat sink capsules for controlling transient temperature response in fuel rodlets, and an innovative approach to high throughput irradiation of transient sensors and instrumentation. The MARCH system’s capabilities will also set the foundation for fuel safety research performed in larger integral-scale test devices with coolant environments representing reactor plants. Based upon historic approaches, but modernized to meet current nuclear technology needs, these larger irradiation devices include flowing pressurized water (including the ability to depressurize to steam) as well liquid metal cooling loops for various fuel rod and small bundle specimens. Here, this paper describes the recently-established MARCH system and current trajectory to enabling advanced transient science with a suite of irradiation test devices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Novel imaging techniques of rectal cancer: what do radiomics and radiogenomics have to offer? A literature review

Introduction: As computational capabilities have advanced, radiologists and their collaborators have looked for novel ways to analyze diagnostic images. This has resulted in the development of radiomics and radiogenomics as new fields in medical imaging. Radiomics and radiogenomics may change the practice of medicine, particularly for patients with colorectal cancer. Radiomics corresponds to the extraction and analysis of numerous quantitative imaging features from conventional imaging modalities in correlation with several endpoints, including the prediction of pathology, genomics, therapeutic response, and clinical outcome. In radiogenomics, qualitative and/or quantitative imaging features are extracted and correlated with genetic profiles of the imaged tissue. Thus far, several studies have evaluated the use of radiomics and radiogenomics in patients with colorectal cancer; however, there are challenges to be overcome before its routine implementation including challenges related to sample size, model design and interpretability, and the lack of robust multicenter validation set. Material and methods: In this article, we will review the concepts of radiomics and radiogenomics and their potential applications in rectal cancer. Conclusion: Radiologists should be aware of the basic concepts, benefits, pitfalls, and limitations of new radiomic and radiogenomics techniques to achieve a balanced interpretation of the results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TOF-SIMS analysis of decoherence sources in superconducting qubits

Superconducting qubits have emerged as a potentially foundational platform technology for addressing complex computational problems deemed intractable with classical computing. Despite recent advances enabling multiqubit designs that exhibit coherence lifetimes on the order of hundreds of μs, material quality and interfacial structures continue to curb device performance. Two-level system defects in the thin superconducting film and adjacent dielectric regions introduce stochastic noise and dissipate electromagnetic energy at the cryogenic operating temperatures. In this study, we utilize time-of-flight secondary ion mass spectrometry to understand the role specific fabrication procedures play in introducing such dissipation mechanisms in these complex systems. We interrogated Nb thin films and transmon qubit structures fabricated through slight modifications in the processing and vacuum conditions. We find that when the Nb film is sputtered onto the Si substrate, oxide and silicide regions are generated at various interfaces. We also observe that impurity species, such as niobium hydrides and carbides, are incorporated within the niobium layer during the subsequent lithographic patterning steps. The formation of these resistive compounds likely impacts the superconducting properties of the Nb thin film. Additionally, we observe the presence of halogen species distributed throughout the patterned thin films. We conclude by hypothesizing the source of such impurities in these structures in an effort to intelligently fabricate superconducting qubits and extend coherence times moving forward.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗