Results for “digital computing” — Page 44

DOE OSTI2026

Nonlinear thermodynamic computing out of equilibrium

We present the design for a thermodynamic computer that can perform arbitrary nonlinear calculations in or out of equilibrium. Simple thermodynamic circuits, fluctuating degrees of freedom in contact with a thermal bath and confined by a quartic potential, display an activity that is a nonlinear function of their input. Such circuits can therefore be regarded as thermodynamic neurons, and can serve as the building blocks of networked structures that act as thermodynamic neural networks, universal function approximators whose operation is powered by thermal fluctuations. We simulate a digital model of a thermodynamic neural network, and show that its parameters can be adjusted by genetic algorithm to perform nonlinear calculations at specified observation times, regardless of whether the system has attained thermal equilibrium. This work expands the field of thermodynamic computing beyond the regime of thermal equilibrium, enabling fully nonlinear computations, analogous to those performed by classical neural networks, at specified observation times.

Whitelam, Stephen [Lawrence Berkeley National Labo↗

DOE OSTI2023

Comparative Study of Variations in Quantum Approximate Optimization Algorithms for the Traveling Salesman Problem

The traveling salesman problem (TSP) is one of the most often-used NP-hard problems in computer science to study the effectiveness of computing models and hardware platforms. In this regard, it is also heavily used as a vehicle to study the feasibility of the quantum computing paradigm for this class of problems. In this paper, we tackle the TSP using the quantum approximate optimization algorithm (QAOA) approach by formulating it as an optimization problem. By adopting an improved qubit encoding strategy and a layer-wise learning optimization protocol, we present numerical results obtained from the gate-based digital quantum simulator, specifically targeting TSP instances with 3, 4, and 5 cities. We focus on the evaluations of three distinctive QAOA mixer designs, considering their performances in terms of numerical accuracy and optimization cost. Notably, we find that a well-balanced QAOA mixer design exhibits more promising potential for gate-based simulators and realistic quantum devices in the long run, an observation further supported by our noise model simulations. Furthermore, we investigate the sensitivity of the simulations to the TSP graph. Overall, our simulation results show that the digital quantum simulation of problem-inspired ansatz is a successful candidate for finding optimal TSP solutions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

Noisy Intermediate-Scale Quantum Applications on a Pathfinder System

Work performed under this one-year LDRD was concerned with estimating resource requirements for small quantum test beds that are expected to be available in the near future. This work represents a preliminary demonstration of our ability to leverage quantum hardware for solving small quantum simulation problems in areas of interest to the DOE. The algorithms enabling such studies are hybrid quantum-classical variational algorithms, in particular the widely-used variational quantum eigensolver (VQE). Employing this hybrid algorithm, in which the quantum computer complements the classical one, we implemented an end-to-end application-level toolchain that allows the user to specify a molecule of interest and compute the ground state energy using the VQE approach. We found significant limitations attributable to the classical portion of the hybrid system, including a greater than greater-than-quartic power scaling of the classical memory requirements with the system size. Current VQE approaches would require an exascale machine for solving any molecule with size greater than 150 nuclei. Our findings include several improvements that we implemented into the VQE toolchain, including a new classical optimizer that is decades old but hadn't been considered before in the VQE ecosystem. Our findings suggest limitations to variational hybrid approaches to simulation that further motivate the need for a gate-based fault-tolerant quantum processor that can implement larger problems using the fully digital quantum phase estimation algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Detectability limitations with 3-D point reconstruction algorithms using digital radiography

The estimated impact of pores in clusters on component fatigue will be highly conservative when based on 2-D rather than 3-D pore positions. To 3-D position and size defects using digital radiography and 3-D point reconstruction algorithms in general require a lower inspection time and in some cases work better with planar geometries than X-ray computed tomography. However, the increase in prior assumptions about the object and the defects will increase the intrinsic uncertainty in the resulting nondestructive evaluation output. In this paper this uncertainty arising when detecting pore defect clusters with point reconstruction algorithms is quantified using simulations. The simulation model is compared to and mapped to experimental data. The main issue with the uncertainty is the possible masking (detectability zero) of smaller defects around some other slightly larger defect. In addition, the uncertainty is explored in connection to the expected effects on the component fatigue life and for different amount of prior object-defect assumptions made.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

TomocuPy – efficient GPU-based tomographic reconstruction with asynchronous data processing

Fast 3D data analysis and steering of a tomographic experiment by changing environmental conditions or acquisition parameters require fast, close to real-time, 3D reconstruction of large data volumes. Here a performance-optimized TomocuPy package is presented as a GPU alternative to the commonly used central processing unit (CPU) based TomoPy package for tomographic reconstruction. TomocuPy utilizes modern hardware capabilities to organize a 3D asynchronous reconstruction involving parallel read/write operations with storage drives, CPU–GPU data transfers, and GPU computations. In the asynchronous reconstruction, all the operations are timely overlapped to almost fully hide all data management time. Since most cameras work with less than 16-bit digital output, the memory usage and processing speed are furthermore optimized by using 16-bit floating-point arithmetic. As a result, 3D reconstruction with TomocuPy became 20–30 times faster than its multi-threaded CPU equivalent. Full reconstruction (including read/write operations and methods initialization) of a 2048 3 tomographic volume takes less than 7 s on a single Nvidia Tesla A100 and PCIe 4.0 NVMe SSD, and scales almost linearly increasing the data size. To simplify operation at synchrotron beamlines, TomocuPy provides an easy-to-use command-line interface. Efficacy of the package was demonstrated during a tomographic experiment on gas-hydrate formation in porous samples, where a steering option was implemented as a lens-changing mechanism for zooming to regions of interest.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic

We introduce a quantum information theory-inspired method to improve the characterization of many-body Hamiltonians on near-term quantum devices. We design a new class of similarity transformations that, when applied as a preprocessing step, can substantially simplify a Hamiltonian for subsequent analysis on quantum hardware. By design, these transformations can be identified and applied efficiently using purely classical resources. In practice, these transformations allow us to shorten requisite physical circuit-depths, overcoming constraints imposed by imperfect near-term hardware. Importantly, the quality of our transformations is t u n a b l e : we define a 'ladder' of transformations that yields increasingly simple Hamiltonians at the cost of more classical computation. Using quantum chemistry as a benchmark application, we demonstrate that our protocol leads to significant performance improvements for zero and finite temperature free energy calculations on both digital and analog quantum hardware. Specifically, our energy estimates not only outperform traditional Hartree-Fock solutions, but this performance gap also consistently widens as we tune up the quality of our transformations. In short, our quantum information-based approach opens promising new pathways to realizing useful and feasible quantum chemistry algorithms on near-term hardware.

Physics↗

DOE OSTI2020

Additive Manufacturing of Heat Pipes for Microreactor Applications

Heat pipes are highly effective devices used to passively transport heat by two-phase capillary action. Their small footprint, light weight and lack of moving parts make them ideal for transportable nuclear microreactors, where size and weight are limited, minimal to no operation and maintenance are required, and high reliability is desired. The use of additive manufacturing allows for the fabrication of heat pipes with performance enhancements, such as microchannels, grooves, arteries, or tailored porosity, which are difficult, expensive or impossible to achieve with traditional fabrication techniques. We are evaluating the capabilities of the Admaflex 130 Digital Light Printer to produce these geometries by characterizing feature shrinkage, developing an optimal heat treatment recipe, assessing the effects of heat treatment atmosphere and varying print orientation. Computational simulations are being used to estimate performance of the various 3D printed configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Fully Homomorphic Encryption

This code implements a Fully Homomorphic Encryption (FHE) system, enabling secure computation on encrypted data without requiring decryption. It supports encryption, decryption, and homomorphic operations like matrix multiplication and addition. This code is adaptable for integrating FHE into linear-time invariant (LTI) systems, including digital control and filtering. With proper configuration from subject matter expertise, encrypted system parameters and signals can be manipulated to perform tasks like state updates, output calculations, and convolution in the encrypted domain. By preserving the structure of LTI systems while ensuring privacy, the framework facilitates secure applications in areas such as autonomous systems, signal processing, and industrial automation. The code initializes the encryption system using parameters provided in the env dictionary. These parameters include the ciphertext modulus, key dimension, plaintext fixed-point scaling factor, and noise bound. During initialization, a secret key is generated, which is essential for encrypting and decrypting data securely. The modular design allows users to tailor these parameters to specific use cases or security requirements. The code implements multiple cryptographic schemes. The learning with errors (LWE) encryption method encodes cleartext message to their plaintext fixed-point representation then encrypted into ciphertext space with additive noise. This noise ensures the security of the scheme, relying on the computational hardness of the LWE problem. The code also includes the Gentry-Sahai-Waters (GSW) scheme based off the LWE problem. Homomorphic matrix multiplication is performed between the LWE and GSW to encrypted data. This is achieved using a decomposition function on the LWE ciphertext during the multiplication operation. For higher-dimensional data, the code includes a method to encrypt entire matrices (GSWMat) using GSW encryption. These encrypted matrices can then be used for homomorphic matrix multiplications (MatMult). The decryption function uses the secret key to recover the original plaintext, removing the added noise and scaling that was originally applied during encryption.

Lois, Roberts [Idaho National Laboratory (INL), Id↗

DOE OSTI2022

Cyber-Informed Engineering for Nuclear Reactor Digital Instrumentation and Control

As nuclear reactors transition from analog to digital technology, the benefits of enhanced operational capabilities and improved efficiencies are potentially offset by cyber risks. Cyber-Informed Engineering (CIE) is an approach that can be used by engineers and staff to characterize and reduce new cyber risks in digital instrumentation and control systems. CIE provides guidance that can be applied throughout the entire systems engineering lifecycle, from conceptual design to decommissioning. In addition to outlining the use of CIE in nuclear reactor applications, this chapter provides a brief primer on nuclear reactor instrumentation and control and the associated cyber risks in existing light water reactors as well as the digital technology that will likely be used in future reactor designs and applications.

42 ENGINEERING↗

DOE OSTI2016

WE-G-209-01: Digital Radiography

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-02: CT

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-03: PET

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-G-209-04: MRI

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Development and Validation of a Simulation Testbed for the Intelligent Building Agents Laboratory (IBAL) Using TRNSYS

This paper documents the development and validation of a dynamic primary cooling and thermal storage system simulation testbed. The system simulation testbed, sIBAL, is based on the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), which is a research infrastructure and testbed for the development, evaluation, and demonstration of intelligent control algorithms. The sIBAL testbed developed in this project will serve as a virtual twin of the real facility for future control algorithm development. The details of the methodologies used to develop and validate the simulation testbed, which replicates the dynamic behaviors of the primary cooling and ice storage system in the IBAL facility, are presented. The simulation testbed was developed in TRNSYS using built-in component models and MATLAB functions to replicate the two water-cooled chillers, a thermal storage tank, pumps, valves and other components for four different operation modes. Experiments on IBAL components were designed and executed to generate experimental data for model development and verification of the simulation platform. The validation of the simulation results was carried out in two phases: 1) independent component simulations for the chillers and thermal storage tank, and 2) a combined testbed simulation of the entire hydronic system. Comparison of simulation results to the experimental data obtained from the IBAL facility showed errors within 1 °C for the temperatures outputs of both the chiller and the thermal storage model. The error is within an acceptable range for further intelligent control algorithms development. The findings from the study are summarized and presented along with areas where additional research is needed. In addition, data filtering procedures and model refinement measures utilized to improve the accuracy and accelerate the computation time of the simulation are presented.

cooling systems↗

DOE OSTI2025

Experimental data for damage mechanics simulation challenge

While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.

3-point bending↗

DOE OSTI2017

Miniature, mobile X-ray computed radiography system

A miniature, portable x-ray system may be configured to scan images stored on a phosphor. A flash circuit may be configured to project red light onto a phosphor and receive blue light from the phosphor. A digital monochrome camera may be configured to receive the blue light to capture an article near the phosphor.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗