SEARCH · Engineering Papers

Results for “information computation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Fast and noise-tolerant determination of the center of rotation in tomography

High-quality tomographic reconstruction is not possible without the accurate localization of the center of rotation. Poor localization leads to artifacts in the data and can even cause reconstructions to fail. There are many approaches to solving this problem, some of which involve the collection of full sinograms, or even provisional tomographic reconstructions, in order to determine the center of rotation. Here, a simple method based on the expected symmetry of the Fourier transform of summed projections approximately 180° apart is presented; unlike cross-correlation methods, it requires only a single Fourier transform to compute, and uses mainly low spatial frequency information which is less susceptible to noise. This approach is shown to be fast, and robust against poor signal-to-noise as well as to projection images acquired at angles that are not exactly 180° apart. This rapid method can be useful as a first step in the processing of tomographic data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

OpenStudio® HPXML workflow [SWR-25-13]

OpenStudio-HPXML allows running residential EnergyPlus™ simulations using an HPXML file for the building description. It is intended to be used by user interfaces or other automated software workflows that automatically produce the HPXML file. OpenStudio-HPXML can accommodate a wide range of different building technologies and geometries. End-to-end simulations typically run in 3-10 seconds, depending on complexity, computer platform and speed, etc. For more information on running simulations, generating HPXML files with the appropriate inputs to run EnergyPlus, etc., please visit the documentation linked below. https://openstudio-hpxml.readthedocs.io/en/latest

Horowitz, Scott↗

DOE OSTI2026

RC-SFA Data Management Templates and Guidance for Standardized, Reusable AI-Ready Data Packages

This data package provides templates and supporting documentation developed by the River Corridor Science Focus Area (RC-SFA; https://www.pnnl.gov/projects/river-corridor) to communicate its approach to managing and publishing AI-ready data. The package is intended to help data users and data producers understand the structures, metadata practices, and quality-control approaches that support consistent, reusable, and machine-actionable data products across RC-SFA studies. Rather than focusing on a single experimental dataset, this package documents the data management framework used to make RC-SFA data easier to find, ingest, navigate, and interpret. The materials in this package reflect RC-SFA practices for standardized data package organization, including the use of a human- and machine-readable README, file-level metadata, data dictionaries, descriptive file naming, method identifiers, and automated and review-based quality assurance procedures. Together, these components illustrate how RC-SFA extends FAIR data principles toward AI-readiness by prioritizing deep metadata, consistency across data packages, and support for informed downstream reuse by both humans and computational tools. This dataset is comprised of (1) readme; (2) presentation slides with an overview of RC-SFA approach and guidance; (3) document of RC-SFA best practices; (4) data dictionary (dd); (5) file level metadata (flmd); and a subfolder containing templates for dd and flmd. All files are .csv and .pdf. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

AI-readiness↗

DOE OSTI2024

QPress: Quantum Press for Next-Generation Quantum Information Platforms

Quantum information science (QIS) holds promise for revolutionizing computation, communication, and sensing. Of course, realizing this promise requires material platforms that can host quantum bits with pre-assigned characteristics that are uniquely attuned to such functionalities. For example, quantum bits for computation should be as immune as possible to any external perturbation, controllable on short time scales and scalable. In contrast, quantum bits for local metrology should be as small as possible and sensitive to specific fields of interest. While tremendous advances in QIS have been achieved in recent years, the underlying properties of the materials that host these quantum bits remains one of the key limitations in their performance.

36 MATERIALS SCIENCE↗

DOE OSTI2025

From Structured Solvents to Hybrid Materials (SS2HM) for Chemically Selective Capture and Electromagnetic Release of CO 2 : Mechanisms, Stability and Interfaces (Final Report)

The goal of this research program was to develop high capacity sorbents amenable for alternative regeneration approaches for direct air capture (DAC) of CO 2 . In particular, the research aimed to develop an understanding of CO 2 binding mechanism, thermal and oxidative stability, and regeneration energetics of functionalized ionic liquids (ILs), deep eutectic solvents (DESs), and porous materials. ILs and DESs are high-dielectric solvents with structural tunability that permits the rational-design for energy-efficient regeneration approaches based on electromagnetic (EM) field and moisture-swing. By further incorporating these solvents into polymeric capsules and other structural supports, multi-scale interfaces for targeted CO 2 and energy transfers were achieved. Aspects related to CO 2 capacity, selectivity, stability, dielectric properties, and binding energies were examined through experimental and computational design to identify molecular descriptors to inform future design of structured solvents and hybrid materials for DAC. Enclosed final report details the key findings, science advancements, and workforce development efforts from this project.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Arrangements for communicating data in a computing system using multiple processors

Systems and methods for reducing data movement in a computer system. The systems and methods use information or knowledge about the structure of an algorithm, operations to be executed at a receiving processing unit, variables or subsets or groups of variables in a distributed algorithm, or other forms of contextual information, for reducing the number of bits transmitted from at least one transmitting processing unit to at least one receiving processing unit or storage device.

Gonzalez, Juan Guillermo↗

DOE OSTI2023

Arrangements for communicating and processing data in a computing system

Gonzalez, Juan Guillermo↗

DOE OSTI2025

Certifying almost all quantum states with few single-qubit measurements

Certifying that an n -qubit state synthesized in the laboratory is close to a given target state is a fundamental task in quantum information science. However, existing rigorous protocols applicable to general target states have potentially prohibitive resource requirements in the form of either deep quantum circuits or exponentially many single-qubit measurements. Here we prove that almost all n -qubit target states, including those with exponential circuit complexity, can be certified from only O ( n 2 ) single-qubit measurements. Given access to the target state’s amplitudes, our protocol requires only O ( n 3 ) classical computation. This result is established by a technique that relates certification to the mixing time of a random walk. Our protocol has applications for benchmarking quantum systems, for optimizing quantum circuits to generate a desired target state and for learning and verifying neural networks, tensor networks and various other representations of quantum states using only single-qubit measurements. We show that such verified representations can be used to efficiently predict highly non-local properties of a synthesized state that would otherwise require an exponential number of measurements on the state. We demonstrate these applications in numerical experiments with up to 120 qubits and observe an advantage over existing methods such as cross-entropy benchmarking.

information theory and computation↗

DOE OSTI2025

BBN-simple: How to bake a universe-sized cake

Big Bang Nucleosynthesis (BBN), the process of creation of lightest elements in the early universe, is a highly robust, precise, and ultimately successful theory that forms one of the three pillars of the standard hot-Big-Bang cosmological model. Existing theoretical treatments of BBN and the associated computer codes are accurate and flexible, but are typically highly technical and opaque, and not suitable for pedagogical understanding of the BBN. Here we present BBN-simple - a from-scratch numerical calculation of the lightest element abundances pitched at an advanced undergraduate or beginning graduate level. We review the physics of the early universe relevant for BBN, provide information about the reaction rates, and discuss computational-mathematics background that is essential in setting up a BBN calculation. Here, we calculate the abundances of the principal nuclear species in a standard cosmological model, and find a reasonably good agreement with public precision-level BBN codes.

Big bang nucleosynthesis↗

DOE OSTI2022

Verification of MOOSE/Bison's Heat Conduction Solver Using Combined Spatiotemporal Convergence Analysis

Bison is a computational physics code that uses the finite element method to model the thermo-mechanical response of nuclear fuel. Since Bison is used to inform high-consequence decisions, it is important that its computational results are reliable and predictive. One important step in assessing the reliability and predictive capabilities of a simulation tool is the verification process, which quantifies numerical errors in a discrete solution relative to the exact solution of the mathematical model. One step in the verification process—called code verification—ensures that the implemented numerical algorithm is a faithful representation of the underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. In this paper, the code verification process is applied to spatiotemporal heat conduction problems in Bison. Simultaneous refinement of the discretization in space and time is employed to reveal any potential mistakes in the numerical algorithms for the interactions between the spatial and temporal components of the solution. For each verification problem, the correct spatial and temporal order of accuracy is demonstrated for both first- and second-order accurate finite elements and a variety of time-integration schemes. Furthermore, these results provide strong evidence that the Bison numerical algorithm for solving spatiotemporal problems reliably represents the underlying mathematical model in MOOSE. The selected test problems can also be used in other simulation tools that numerically solve for conduction or diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Hybrid Entanglement Distribution between Remote Microwave Quantum Computers Empowered by Machine Learning

Superconducting microwave circuits with Josephson junctions, the major platform for quantum computing, can only reach the full capability when connected. This requires an efficient protocol to distribute microwave entanglement. While quantum computers typically use discrete-variable (DV) methods for information encoding, the entire continuous-variable (CV) degree of freedom in electromagnetic fields must be utilized to achieve the highest entanglement distribution rate. Here, we propose a hybrid protocol to resolve the incompatibility between DV microwave quantum computers and CV quantum communications. CV microwave entanglement is distributed using optical swapping of optical-microwave entanglement pairs. To interface with DV microwave quantum computers, we further design a hybrid circuit to simultaneously convert and distill high-quality DV entanglement from noisy CV entanglement. The hybrid circuit is trained with machine-learning algorithms, ensuring high entanglement fidelity and generation rate. In conclusion, our work not only provides a practical method to realize efficient quantum links for superconducting microwave quantum computers, but also opens avenues to bridge the gap between DV and CV quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Integration of software tools for integrative modeling of biomolecular systems

Integrative modeling computes a model based on varied types of input information, be it from experiments or prior models. Often, a type of input information will be best handled by a specific modeling software package. In such a case, we desire to integrate our integrative modeling software package, Integrative Modeling Platform (IMP), with software specialized to the computational demands of the modeling problem at hand. After several attempts, however, we have concluded that even in collaboration with the software's developers, integration is either impractical or impossible. The reasons for the intractability of integration include software incompatibilities, differing modeling logic, the costs of collaboration, and academic incentives. In the integrative modeling software ecosystem, several large modeling packages exist with often redundant tools. So we reason, therefore, that the other development groups have similarly concluded that the benefit of integration does not justify the cost. As a result, modelers are often restricted to the set of tools within a single software package. The inability to integrate tools from distinct software negatively impacts the quality of the models and the efficiency of the modeling. As the complexity of modeling problems grows, we seek to galvanize developers and modelers to consider the long-term benefit that software interoperability yields. In this article, we formulate a demonstrative set of software standards for implementing a model search using tools from independent software packages and discuss our efforts to integrate IMP and the crystallography suite Phenix within the Bayesian modeling framework.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Quantum networks with neutral atom processing nodes

Abstract Quantum networks providing shared entanglement over a mesh of quantum nodes will revolutionize the field of quantum information science by offering novel applications in quantum computation, enhanced precision in networks of sensors and clocks, and efficient quantum communication over large distances. Recent experimental progress with individual neutral atoms demonstrates a high potential for implementing the crucial components of such networks. We highlight latest developments and near-term prospects on how arrays of individually controlled neutral atoms are suited for both efficient remote entanglement generation and large-scale quantum information processing, thereby providing the necessary features for sharing high-fidelity and error-corrected multi-qubit entangled states between the nodes. We describe both the functionality requirements and several examples for advanced, large-scale quantum networks composed of neutral atom processing nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Powering DNA strand-displacement reactions with a continuous flow reactor

Living systems require a sustained supply of energy and nutrients to survive. These nutrients are ingested, transformed into low-energy waste products, and excreted. In contrast, synthetic DNA strand-displacement reactions typically run within closed systems provided with a finite initial supply of reactants. Once the reactants are consumed, all net reactions halt and the system ceases to function. In the study, we ran DNA strand-displacement reactions in a continuous flow reactor, infusing fresh reactants and withdrawing waste, enabling the system to dynamically update its outputs in response to changing inputs. Running DNA strand-displacement reactions inside of continuous flow reactors allows the system to be re-used for multiple rounds of computation, which could enable the execution of more elaborate information processing tasks, including single-rail negation and sequential logic circuits.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Variable Precision Computing (VPC) (Final Report)

The overall goal of the Variable Precision Computing project is exploring and identifying ways to reduce internodal communication cost in production physics simulation experiments running on a distributed-memory systems by compressing data, either in a lossy or lossless way, thus resulting in a significant computational performance increase. Among the several approaches proposed, the one discussed here has been proposed, designed and implemented by me. It concerns the application of information theory-derived metrics to classical molecular dynamics and computational fluid dynamics simulation experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Nowcasting Earthquakes With Stochastic Simulations: Information Entropy of Earthquake Catalogs

Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes can be computed using Receiver Operating Characteristic methods. Furthermore, analysis of the Shannon information content of the earthquake catalogs has been used to show that there is information contained in the catalogs, and that it can vary in time. So an important question remains, where does the information originate? In this paper, we examine this question using stochastic simulations of earthquake catalogs. Our catalog simulations are computed using an Earthquake Rescaled Aftershock Seismicity (“ERAS”) stochastic model. This model is similar in many ways to other stochastic seismicity simulations, but has the advantage that the model has only 2 free parameters to be set, one for the aftershock (Omori-Utsu) time decay, and one for the aftershock spatial migration away from the epicenter. Generating a simulation catalog and fitting the two parameters to the observed catalog such as California takes only a few minutes of wall clock time. While clustering can arise from random, Poisson statistics, we show that significant information in the simulation catalogs arises from the “non-Poisson” power-law aftershock clustering, implying that the practice of de-clustering observed catalogs may remove information that would otherwise be useful in forecasting and nowcasting. We also show that the nowcasting method provides similar results with the ERAS model as it does with observed seismicity.

58 GEOSCIENCES↗

DOE OSTI2023

Experimental measurement of the effective contact angle for solvent/packing interactions in a structured packed column for CO 2 capture

The contact angle is a critical factor for determining the effective mass transfer area for carbon dioxide (CO 2 ) capture via the chemical absorption process in a packed column, and thus the overall capture efficiency of the packed column. Many widely used commercial packings involve microscale features (perforation, corrugation, etc.) that may also affect the wetting behavior. This study proposes a systematic method of using a modified Wilhelmy plate to measure the effective contact angle to characterize the solvent and featured packing interaction. In lieu of computational efforts relying on assumptions guided by semi-informed correlation, the proposed method directly measures the effective contact angle as a function of the solvent and packing thermophysical and hydrodynamic properties. The characterization of the effective contact angle is then integrated in the computational fluid dynamics modeling to reduce uncertainty in the prediction of effective mas transfer area. Experiments were conducted for stainless steel coupons using water and aqueous sodium hydroxide (NaOH) solvent for verification of the proposed experimental protocol. The surface tension of the aqueous NaOH solvent was altered using surfactant and antifoam. The effective contact angle increases with the increased value of the surface tension for flat stainless steel sheets. On the other hand, effective contact angles do not vary in Mellapak coupons for aqueous monoethanolamine (MEA) and NaOH solvent. In this case, surface textures and sheet design play a dominant role in the surface tension of solvents. Furthermore, CO 2 loading has a significant effect on the contact angle for Mellapak coupons. As expected, the contact angle decreases with the increasing temperature of CO 2 capture solvents (MEA, EEMPA). The effective contact angle measurement using the Wilhelmy plate method can provide more accurate and efficient solvents for characterizing the solvent-packing surface interactions. Subsequently, the present method enhances the accuracy of the prediction of the effective mass transfer area in carbon capture by solvent absorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗