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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Nuclear, Land marker for a Waste Isolation Site: International Architecture Competition - 18240

The design and construction of a nuclear waste marker must include many architectural considerations. Very little research has been conducted by architects to address this issue to date. Historically, the task of designating a nuclear waste site has been a discussion predominantly contained within the scientific and engineering communities. In an effort to engage architects within this dialogue, arch out loud hosted the NUCLEAR competition as an international, architectural investigation into the design of a nuclear waste site marker. The NUCLEAR competition asks participants to design a marker to designate the site of the Waste Isolation Pilot Plant (WIPP) located near Carlsbad, New Mexico. The marker will be meant to be a means of passive institutional controls (PICs) to deter inadvertent human intrusion upon the site and should last 10,000 years. The NUCLEAR competition defined the purpose of the nuclear waste site marker as a means to communicate the danger of inadvertent intrusion from future generations. The competition requires that entries must be both legible in communication and durable in their construction. The competition brief challenged participants to consider how customs and languages will evolve over time and to predict what motivations future generations might have for digging at the site. Other background information was provided about the site such as how waste was stored and how the unique geology of the site seals the waste. The 1993 Sandia National Laboratories report titled Expert Judgment on Markers to Deter Inadvertent Human Intrusion into the Waste Isolation Pilot Plant [1] was referenced along with the 1992 WIPP Land Withdrawal Act [2], interviews with WIPP scientists [3] involved with the WIPP PICs program and the Nuclear Energy Agency Records Knowledge and Memory working group. Competition participants were given digital 3-D Computer-Aided Design models for reference that included the underground storage portion of the site, existing buildings and the 16-square-mile site boundary identified in the 1992 WIPP Land Withdrawal Act [2]. This paper will: - Provide a detailed description of the submitted proposals including graphic analysis of the visualizations, diagrams, technical drawings, jury comments and statements. - Catalogue and identify the consistent themes within all submissions with possible categories including: 1) overall architectural form and language, 2) integration of written language and symbols within architecture, 3) use of technology and robotics, 4) construction methods and materials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

MPF X-Ray Module Setup for 2018

The Mobile Plutonium Facility (MPF) is a portable module design facility that can be deployed anywhere in the world for the safe recovery, packaging, and shipment of a nations legacy, or excess plutonium stockpile. All of the modules of MPF have specific purposes for operating in a mission if one were to ever come up. For my past four internships here at SRNL I have been working on the support of the X-Ray module for MPF. This year I installed new equipment I had purchased last year for the X-Ray Module and made sure the module was mission ready for the chance that the team deploys in the future for plutonium recovery. Using digital radiography (DR) and computed tomography (CT) provides the MPF team the ability to verify the contents of containers that would be holding material. This also ensures the safety of the team members in the glovebox facilities by verifying that there are no sharps, liquids, or other items that may harm the workers or glovebox operations when working with radioactive material. X-Ray imaging can also pick up low density objects like plastic bags and tape. Note how the DR image hides the puncture in the inner can while the CT image shows the damage. New DR and CT computers with upgraded software, New imaging panel, NOVO Portable X-Ray System. Because of the new upgrades to the X-Ray module system containers can be scanned and evaluated quicker than before. With the last system the 3D model reconstruction alone would take anywhere from 10-12 minutes, now with the new system that time has been brought down to just shy of 1 minute 30 seconds. The new portable system also can 1,2 or 4 images of an object and stitch them together into a mosaic for scanning of larger containers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Development of a new IEC Standard on cybersecurity controls for I and C in Nuclear Power Plants - IEC 63096 - 158

Standards are promoting the enhancement of cybersecurity in Nuclear Power Plants (NPP). Standardizing processes and procedures are also crucial to achieve successful international collaboration. Many information security standards were developed in recent years; however, not many of them could be directly applied to NPPs. This paper provides an overview of the development of a new cybersecurity standard dealing with cybersecurity controls for nuclear power plants around the world. For I and C systems in NPPs, the new IEC 63096 standard targeted for issue in 2019, focuses specifically on the selection and application of cybersecurity controls from the included security controls catalogue. The role of selected and applied cybersecurity controls is to prevent, detect and react to digital attacks against computer-based I and C systems. This standard applies to the I and C of new nuclear power plants and to the I and C modernization in existing plants. It is being prepared and based on IEC 62645 , ISO/IEC 27000 series , IAEA , and country specific guidance in this expanding the technical and the security focus area. The Standard is intended to be used by designers and operators of NPPs (utilities), systems evaluators, vendors and subcontractors, and by licensors. While the development of international standards is essential it is also a lengthy process, taking multiple years. Especially with regard to cybersecurity, all involved stakeholders have to collaborate. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Downhole MCA for High-Resolution Spectral Gamma Logging for Characterization of Radiological Contaminants - 16321

A downhole data system for spectral gamma ray detectors has been developed and deployed in boreholes at the US DOE Hanford Site in southeastern Washington State. This system consists of a digital multichannel analyzer, power supply, and high-voltage power supply located in the borehole probe. Communication up the cable to a computer at the surface is digital, meaning that issues related to analog pulse transmission over the logging cable are eliminated. This system can support either scintillator or solid-state detectors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Multistate resistance in TaN/(Hf,Zr)O 2 /Ta ferroelectric tunnel junctions

Ferroelectric tunnel junctions (FTJs) utilizing hafnium zirconium oxide (HZO) have emerged as promising non-volatile memory elements for microelectronics, compatible with back end of line (BEOL) complementary–metal–oxide semiconductor fabrication. This study investigates asymmetric electrode TaN/HZO/Ta devices with a 6 nm thick HZO layer as FTJs for multistate resistive memory applications. The individual FTJs exhibit a resistance ratio exceeding 10× when utilized as a binary state device, with pulsing between −1.7 and +1.4 V to set the high resistance state (HRS) and low resistance state (LRS), respectively. Following with reduced write voltage pulses allows the ferroelectric device to operate with a selection of over 32 distinct resistance states (2 5 bits) between the LRS and HRS. This work then explores the stability of the resistance states during write/read pulse cycling, along with the stability of the state after multiple read pulses. Accessing the multibit state shows stability within 50 reads with the binary state remaining stable for more than 4000 reads pulses. With their multistate tunability and versatility, FTJs hold promise as BEOL memory elements for compute-in-memory (CiM) arrays, binary digital memory, or weighted vector matrix multiplication applications with low power consumption during computations.

CMOS↗
DOE OSTI2018

Post Moore's Law Report

Moore's law is driving an information revolution, worldwide economic growth, and is a tool for national security. This report explains how dire proclamations that "Moore's law is ending" are due to a natural redefinition of the phrase, but computing remains positioned to both drive economic growth and support national security. The computer industry used to be led by the semiconductor companies that made ever faster microprocessors with larger memories. However, control is shifting to new ways of designing computers, notably based on 3D chips and new analog and digital architectures. While artificial intelligence and quantum computing research have become mainstream pursuits, these latter two areas seem destined split off from Moore's law rather than become a part of it. We include a discussion of recent developments and opportunities in optical communications and computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Infrared intrusion detection system (IRIDS)

A system and method for intrusion detection includes an imager directed towards an object in an interior space. The imager is in data communication with a computer. The computer is arranged to process digital three-dimensional image data received from the imager and programmed to execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object. The computer generates an alarm output in response to detecting movement of the object above a predetermined threshold. The method includes providing an imager directed towards an object in an interior space; receiving Time of Flight signals by the imager; processing digital three-dimensional image data received from the imager; and executing a change detection algorithm in response to the processed three-dimensional data to determine movement of the object.

Russell, John L.↗
DOE OSTI2024

Multichannel meta-imagers for accelerating machine vision

Rapid developments in machine vision technology have impacted a variety of applications, such as medical devices and autonomous driving systems. These achievements, however, typically necessitate digital neural networks with the downside of heavy computational requirements and consequent high energy consumption. As a result, real-time decision-making is hindered when computational resources are not readily accessible. Here we report a meta-imager designed to work together with a digital back end to offload computationally expensive convolution operations into high-speed, low-power optics. Further, in this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positively and negatively valued convolution operations in a single shot. We use our meta-imager for object classification, achieving 98.6% accuracy in handwritten digits and 88.8% accuracy in fashion images. Owing to its compactness, high speed and low power consumption, our approach could find a wide range of applications in artificial intelligence and machine vision applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

A Digital Twin of Scalable Quantum Clouds

Quantum computing has emerged as a transformative technology capable of solving complex problems beyond the limit of classical systems. The rapid development of quantum processors has led to the proliferation of cloud-based quantum computing services offered by platforms such as IBM, Google, and Amazon. These platforms introduce unique challenges in resource allocation, job scheduling, and multi-device orchestration as quantum workloads become increasingly complex. In this work, we present a digital twin of quantum cloud infrastructures: a framework designed to model and simulate the behavior of real quantum cloud systems. Developed in Python using the SimPy discrete-event simulation library, the framework replicates key aspects of quantum cloud environments, including detailed quantum device modeling, job lifecycle management, and job fidelity. It incorporates noise-aware fidelity estimation, making it the first of its kind to simulate superconducting gate-based quantum cloud systems at an administrative level with job fidelity. We present use cases as proof of concept, demonstrating that our quantum cloud simulation framework can act as a digital twin of a quantum cloud and support the modeling and implementation of practical systems.

Luo, Waylon [Kent State University]↗
DOE OSTI2025

Quantitative Comparisons of Image Quality for Flash X-Ray Detectors

Due to X-rays’ ability to penetrate materials, flash X-ray radiography can be used for high-speed measurements where direct optical access is not possible. Choice of detector has a pronounced impact on resulting image quality. Four different detector systems were evaluated with a 450kVp flash source to quantitatively compare image quality metrics. The scintillating digital detector had less image noise than the three different storage phosphor computed radiography detectors across all transmission levels, but lacked the spatial resolution of the computed radiography detectors. For the screens tested here, the HPX-DR digital system had the highest signal to noise ratio of 68.24 and contrast to noise ratio of 35.53, but had the lowest spatial resolution, resolving 2.5 line pairs per millimeter at 1.78% contrast. At a value of 37.59, the Flex GP imaging plate had a signal to noise value above its storage phosphor counterparts under a 450kVp flash source. For radiographic setups typically used for dynamic experiments, the Flex XL Blue and Flex HR detectors had signal to noise ratios of 18.44 and 26.56 respectively. The highest resolved spatial frequencies of the Flex GP, Flex XL Blue, and Flex HR with the flash source are 3.85, 5.00, and 3.85 line pairs per millimeter, respectively. In conclusion, the Flex GP detector had the best combination of signal to noise ratio, contrast to noise ratio, and spatial resolution under a flash source.

computed radiography↗
DOE OSTI2017

Building blocks for a digital twin of additive manufacturing

Properties and serviceability of additively manufactured components are affected by their geometry, microstructure and defects. These important attributes are now optimized by trial and error because the essential process variables cannot currently be selected from scientific principles. A recourse is to build and rigorously validate a digital twin of the additive manufacturing process that can provide accurate predictions of the spatial and temporal variations of metallurgical parameters that affect the structure and properties of components. Key building blocks of a computationally efficient first-generation digital twin of laser-based directed energy deposition additive manufacturing utilize a transient, three-dimensional model that calculates temperature and velocity fields, cooling rates, solidification parameters and deposit geometry. The measured profiles of stainless steel 316L and Alloy 800H deposits as well as the secondary dendrite arm spacing (SDAS) and Vickers hardness measurements are used to validate the proposed digital twin. The predicted cooling rates, temperature gradients, solidification rates, SDAS and micro-hardness values are shown to be more accurate than those obtained from a commonly used heat conduction calculation. Finally, these metallurgical building blocks serve as a phenomenological framework for the development of a digital twin that will make the expanding knowledge base of additive manufacturing usable in a practical way for all scientists and engineers.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Estimation of full-field, full-order experimental modal model of cable vibration from digital video measurements with physics-guided unsupervised machine learning and computer vision

Cables are critical components for a variety of structures such as stay cables and suspenders of cable-stayed bridges and suspension bridges. When in operational service, they are vulnerable to cumulative fatigue damage induced by dynamic loads (e.g., the cyclic vehicle loads and wind excitation). To accurately analyze and predict their dynamics behaviors and performance that could be spatially local and temporal transient, it is essential to perform high-resolution vibration measurements, from which their dynamics properties are identified and, subsequently, a high spatial resolution, full-modal-order dynamics model of cable vibration can be established. In this study, we develop a physics-guided, unsupervised machine learning-based video processing approach that can blindly and efficiently extract the full-field (as many points as the pixel number of the video frame) modal parameters of cable vibration using only the video of an operating (output-only) cable. In particular, by incorporating the physics of cable vibration (taut string model), a novel automated modal motion filtering method is proposed to enable autonomous identification of full-order (as many modes as possible) dynamic parameters, including those weakly excited modes that used to be challenging to identify in operational modal analysis. Therefore, a full-field, full-order modal model of cable vibration is established by the proposed method. Furthermore, this new approach provides a low-cost and noncontact technique to estimate the cable tension using only the video of the vibrating cable where the fundamental frequency is automatically and efficiently estimated to compute the cable tension according to the taut string equation. Laboratory experiments on a bench-scale cable are conducted to validate the developed approach.

42 ENGINEERING↗
DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Meta-optic accelerators for object classifiers

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision-making when computation resources are limited. Here, we demonstrate a meta-optic–based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems, resulting in a robust classifier that achieves 93.1% accurate classification of handwriting digits and 93.8% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine vision and artificial intelligence.

42 ENGINEERING↗
DOE OSTI2020

The potential of quantum annealing for rapid solution structure identification

Abstract The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations of unquestionable performance gains leveraging novel hardware platforms have faced significant obstacles. One key challenge is understanding the algorithmic properties that distinguish such devices from established optimization approaches. Through the careful design of contrived optimization tasks, this work provides new insights into the computation properties of quantum annealing and suggests that this model has the potential to quickly identify the structure of high-quality solutions. A meticulous comparison to a variety of algorithms spanning both complete and local search suggests that quantum annealing’s performance on the proposed optimization tasks is distinct. This result provides new insights into the time scales and types of optimization problems where quantum annealing has the potential to provide notable performance gains over established optimization algorithms and suggests the development of hybrid algorithms that combine the best features of quantum annealing and state-of-the-art classical approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

End-to-end AI framework for interpretable prediction of molecular and crystal properties

We introduce an end-to-end computational framework that allows for hyperparameter optimization using the DeepHyper library, accelerated model training, and interpretable AI inference. The framework is based on state-of-the-art AI models including CGCNN, PhysNet, SchNet, MPNN, MPNN-transformer, and TorchMD-NET. We employ these AI models along with the benchmark QM9, hMOF, and MD17 datasets to showcase how the models can predict user-specified material properties within modern computing environments. We demonstrate transferable applications in the modeling of small molecules, inorganic crystals and nanoporous metal organic frameworks with a unified, standalone framework. We have deployed and tested this framework in the ThetaGPU supercomputer at the Argonne Leadership Computing Facility, and in the Delta supercomputer at the National Center for Supercomputing Applications to provide researchers with modern tools to conduct accelerated AI-driven discovery in leadership-class computing environments. We release these digital assets as open source scientific software in GitLab, and ready-to-use Jupyter notebooks in Google Colab.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mode-multiplexed photonic integrated vector dot-product core from inverse design

Photonic computing has the potential to harness the full degrees of freedom (DOFs) of the light field, including the wavelength, spatial mode, spatial location, phase quadrature, and polarization, to achieve a higher level of computing parallelism and scalability than digital electronic processors. While multiplexing using the wavelength and other DOFs can be readily integrated on silicon photonics platforms with compact footprints, conventional mode-division multiplexed (MDM) photonic designs occupy areas exceeding tens to hundreds of microns for a few spatial modes, significantly limiting their scalability. Here, we utilize inverse design to demonstrate an ultracompact photonic computing core that calculates vector dot products based on MDM coherent mixing. Our dot-product core integrates the functionalities of two-mode multiplexers and one multimode coherent mixer within a nominal footprint of 5 μm x 3 μm . We have experimentally demonstrated computing examples on the fabricated dot-product core, including complex number multiplication and motion estimation using optical flow. The compact dot-product core design enables large-scale on-chip integration in a parallel photonic computing primitive cluster for high-throughput scientific computing and computer vision tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform

Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.

42 ENGINEERING↗