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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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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Electrorefining of Zircaloy-4 in LiCl-KCl to Decontaminate Irradiated Cladding - 16238

Electrorefining on unirradiated Zircaloy-4 specimen in LiCl-KCl was performed by managing the anode potential to identify whether high purity zirconium can be recovered in metallic form by electrorefining. Four different concentrations of ZrCl{sub 4} (0.1, 0.5, 1.0 and 2.0 wt%) were tested. Results indicate that high purity metallic zirconium was recovered at low concentration of ZrCl{sub 4} but ZrCl could be recovered at high concentration. The electrorefining experiments were simulated by a three-dimensional computational electrorefining model. Several physical properties were tested, and a set of physical properties was determined in the condition where chemical forms of cathode deposits estimated by the computational model accorded with the experimental results. Using those properties, co-deposition of zirconium and uranium was simulated in the geometry of a preliminary designed electro-refiner for irradiated Zircaloy claddings. Operating conditions that can lead to the formation of zirconium metal without ZrCl and uranium were calculated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Computing for the DUNE Long-Baseline Neutrino Oscillation Experiment

This is a talk given at Computers in High Energy Physics in Adelaide, South Australia, Australia in November 2019. It is partially intended to explain the context of DUNE Computing for computing specialists. The DUNE collaboration consists of over 180 institutions from 33 countries. The experiment is in preparation now with commissioning of the first 10kT fiducial volume Liquid Argon TPC expected over the period 2025-2028 and a long data taking run with 4 modules expected from 2029 and beyond. An active prototyping program is already in place with a short test beam run with a 700T, 15,360 channel prototype of single-phase readout at the neutrino platform at CERN in late 2018 and tests of a similar sized dual-phase detector scheduled for mid-2019. The 2018 test beam run was a valuable live test of our computing model. The detector produced raw data at rates of up to ~2GB/s. These data were stored at full rate on tape at CERN and Fermilab and replicated at sites in the UK and Czech Republic. In total 1.2 PB of raw data from beam and cosmic triggers were produced and reconstructed during the six week test beam run. Baseline predictions for the full DUNE detector data, starting in the late 2020's are 30-60 PB of raw data per year. In contrast to traditional HEP computational problems, DUNE's Liquid Argon TPC data consist of simple but very large (many GB) 2D data objects which share many characteristics with astrophysical images. This presents opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A Computational Framework for Control Co-Design of Resilient Cyber–Physical Systems With Applications to Microgrids

Critical infrastructure networks, such as power and transportation networks, can be modelled as cyber-physical systems. As the complexity of such systems grow, there is need for developing metrics and design tools that will co-optimize the physical components of the system and the control policies to guarantee resilience against cyber and natural threats. To that end, we develop a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives. Here, the capabilities of the developed co-design engine is demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum simulations of nuclear resonances with variational methods

Background: The many-body nature of nuclear physics problems poses significant computational challenges. These challenges become even more pronounced when studying the resonance states of nuclear systems, which are governed by the non-Hermitian Hamiltonian. Quantum computing, particularly for quantum many-body systems, offers a promising alternative, especially within the constraints of current noisy intermediate-scale quantum (NISQ) devices. Purpose: This work aims to simulate nuclear resonances using quantum algorithms by developing a variational framework compatible with non-Hermitian Hamiltonians and implementing it fully on a quantum simulator. Methods: We employ the complex scaling technique to extract resonance positions classically and adapt it for quantum simulations using a two-step algorithm. First, we transform the non-Hermitian Hamiltonian into a Hermitian form by using the energy variance as a cost function within a variational framework. Second, we perform 𝜃-trajectory calculations to determine optimal resonance positions in the complex energy plane. To address resource constraints on NISQ devices, we utilize Gray code (GC) encoding to reduce qubit requirements. Results: We first validate our approach using a schematic potential model that mimics a nuclear potential, successfully reproducing known resonance energies with high fidelity. We then extend the method to a more realistic 𝛼−𝛼 nuclear potential and compute the 𝐷- and 𝐺-wave resonance energies with a basis size of 𝑁=16, using only four qubits. The quantum simulation results closely match the classical values, demonstrating the feasibility of our approach. Conclusions: This study demonstrates, for the first time, that the complete 𝜃-trajectory method can be implemented on a quantum computer without relying on any classical input beyond the Hamiltonian. The results establish a scalable and efficient quantum framework for simulating resonance phenomena in nuclear systems. This work represents a significant step toward quantum simulations of open quantum systems and lays the foundation for future investigations into resonance structures in nuclear, atomic, and molecular physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗
NASA NTRS1989

A direct procedure for interpolation on a structured curvilinear two-dimensional grid

A direct procedure is presented for locally bicubic interpolation on a structured, curvilinear, two-dimensional grid. The physical (Cartesian) space is transformed to a computational space in which the grid is uniform and rectangular by a generalized curvilinear coordinate transformation. Required partial derivative information is obtained by finite differences in the computational space. The partial derivatives in physical space are determined by repeated application of the chain rule for partial differentiation. A bilinear transformation is used to analytically transform the individual quadrilateral cells in physical space into unit squares. The interpolation is performed within each unit square using a piecewise bicubic spline.

Zingg, David W.↗
NASA NTRS1995

Nanoelectronics: Opportunities for future space applications

Further improvements in the performance of integrated electronics will eventually halt due to practical fundamental limits on our ability to downsize transistors and interconnect wiring. Avoiding these limits requires a revolutionary approach to switching device technology and computing architecture. Nanoelectronics, the technology of exploiting physics on the nanometer scale for computation and communication, attempts to avoid conventional limits by developing new approaches to switching, circuitry, and system integration. This presentation overviews the basic principles that operate on the nanometer scale that can be assembled into practical devices and circuits. Quantum resonant tunneling (RT) is used as the center-piece of the overview since RT devices already operate at high temperature (120 degrees C) and can be scaled, in principle, to a few nanometers in semiconductors. Near- and long-term applications of GaAs and silicon quantum devices are suggested for signal and information processing, memory, optoelectronics, and radio frequency (RF) communication.

Frazier, Gary↗
DOE OSTI2013

Computational nuclear quantum many-body problem: The UNEDF project

The UNEDF project was a large-scale collaborative effort that applied high-performance computing to the nuclear quantum many-body problem. The primary focus of the project was on constructing, validating, and applying an optimized nuclear energy density functional, which entailed a wide range of pioneering developments in microscopic nuclear structure and reactions, algorithms, high-performance computing, and uncertainty quantification. UNEDF demonstrated that close associations among nuclear physicists, mathematicians, and computer scientists can lead to novel physics outcomes built on algorithmic innovations and computational developments. This review showcases a wide range of UNEDF science results to illustrate this interplay.

Configuration interaction↗
DOE OSTI2013

Computational nuclear quantum many-body problem: The UNEDF project

The UNEDF project was a large-scale collaborative effort that applied high-performance computing to the nuclear quantum many-body problem. The primary focus of the project was on constructing, validating, and applying an optimized nuclear energy density functional, which entailed a wide range of pioneering developments in microscopic nuclear structure and reactions, algorithms, high-performance computing, and uncertainty quantification. UNEDF demonstrated that close associations among nuclear physicists, mathematicians, and computer scientists can lead to novel physics outcomes built on algorithmic innovations and computational developments. This review showcases a wide range of UNEDF science results to illustrate this interplay.

Configuration interaction↗
DOE OSTI2015

Methodology comparison for gamma-heating calculations in material-testing reactors

The Jules Horowitz Reactor (JHR) is a Material-Testing Reactor (MTR) under construction in the south of France at CEA Cadarache (French Alternative Energies and Atomic Energy Commission). It will typically host about 20 simultaneous irradiation experiments in the core and in the beryllium reflector. These experiments will help us better understand the complex phenomena occurring during the accelerated ageing of materials and the irradiation of nuclear fuels. Gamma heating, i.e. photon energy deposition, is mainly responsible for temperature rise in non-fuelled zones of nuclear reactors, including JHR internal structures and irradiation devices. As temperature is a key parameter for physical models describing the behavior of material, accurate control of temperature, and hence gamma heating, is required in irradiation devices and samples in order to perform an advanced suitable analysis of future experimental results. From a broader point of view, JHR global attractiveness as a MTR depends on its ability to monitor experimental parameters with high accuracy, including gamma heating. Strict control of temperature levels is also necessary in terms of safety. As JHR structures are warmed up by gamma heating, they must be appropriately cooled down to prevent creep deformation or melting. Cooling-power sizing is based on calculated levels of gamma heating in the JHR. Due to these safety concerns, accurate calculation of gamma heating with well-controlled bias and associated uncertainty as low as possible is all the more important. There are two main kinds of calculation bias: bias coming from nuclear data on the one hand and bias coming from physical approximations assumed by computer codes and by general calculation route on the other hand. The former must be determined by comparison between calculation and experimental data; the latter by calculation comparisons between codes and between methodologies. In this presentation, we focus on this latter kind of bias. Nuclear heating is represented by the physical quantity called absorbed dose (energy deposition induced by particle-matter interactions, divided by mass). Its calculation with Monte Carlo codes is possible but computationally expensive as it requires transport simulation of charged particles, along with neutrons and photons. For that reason, the calculation of another physical quantity, called KERMA, is often preferred, as KERMA calculation with Monte Carlo codes only requires transport of neutral particles. However, KERMA is only an estimator of the absorbed dose and many conditions must be fulfilled for KERMA to be equal to absorbed dose, including so-called condition of electronic equilibrium. Also, Monte Carlo computations of absorbed dose still present some physical approximations, even though there is only a limited number of them. Some of these approximations are linked to the way how Monte Carlo codes apprehend the transport simulation of charged particles and the productive and destructive interactions between photons, electrons and positrons. There exists a huge variety of electromagnetic shower models which tackle this topic. Differences in the implementation of these models can lead to discrepancies in calculated values of absorbed dose between different Monte Carlo codes. The magnitude of order of such potential discrepancies should be quantified for JHR gamma-heating calculations. We consequently present a two-pronged plan. In a first phase, we intend to perform compared absorbed dose / KERMA Monte Carlo calculations in the JHR. This way, we will study the presence or absence of electronic equilibrium in the different JHR structures and experimental devices and we will give recommendations for the choice of KERMA or absorbed dose when calculating gamma heating in the JHR. In a second phase, we intend to perform compared TRIPOLI4 / MCNP absorbed dose calculations in a simplified JHR-representative geometry. For this comparison, we will use the same nuclear data library for both codes (the European library JEFF3.1.1 and photon library EPDL97) so as to isolate the effects from electromagnetic shower models on absorbed dose calculation. This way, we hope to get insightful feedback on these models and their implementation in Monte Carlo codes. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗
NASA NTRS1977

Generation and physical characteristics of the LANDSAT-1, -2 and -3 MSS computer compatible tapes

The generation and format of the LANDSAT 1, 2, and 3 system corrected multispectral scanner computer compatible tapes are discussed. Included in the discussion are the spacecraft sensors, scene characteristics, the transmission of data, and the conversion of the data to computer compatible tapes. Also included in the discussion are geometric and radiometric corrections, tape formats, and the physical characteristics of the tape.

Thomas, V. L.↗