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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗
DOE OSTI2017

Engineered Zircaloy Cladding Modifications for Improved Accident Tolerance of LWR Nuclear Fuel

The DOE NEUP sponsored IRP on accident tolerant fuel (ATF) entitled Engineered Zircaloy Cladding Modifications for Improved Accident Tolerance of LWR Nuclear Fuel involved three academic institutions, Idaho National Laboratory (INL), and ATI Materials (ATI). Detailed descriptions of the work at the University of Illinois (UIUC, prime), the University of Florida (UF), the University of Michigan (UMich), and INL are included in this document as separate sections. This summary provides a synopsis of the work performed across the IRP team. Two ATF solution pathways were initially proposed, coatings on monolithic Zr-based LWR cladding material and selfhealing modifications of Zr-based alloys. The coating pathway was extensively investigated, both experimentally and in computations. Experimental activities related to ATF coatings were centered at UIUC, UF, and UMich and involved coating development and testing, and ion irradiation. Neutronic and thermal hydraulic aspects of ATF coatings were the focus of computational work at UIUC and UMich, while materials science aspects were the focus of computational work at UF and INL. ATI provided monolithic Zircaloy 2 and 4 material and a binary Zr-Y alloy material. The selfhealing pathway was investigated with advanced computations only. Beryllium was identified as a valid self-healing additive early in this work. However, all attempts to fabricate a Zr-Be alloy failed. Several avenues of fabrication were explored. ATI ultimately declined our fabrication request over health concerns associated with Be (we note that Be was not part of the original work scope and the ATI SOW). Likewise, Ames Laboratory declined our fabrication request, citing known litigation dating to the 1980s and 1990s involving the U.S. Federal government and U.S. National Laboratory employees involving the use of Be. Materion (formerly, Brush Wellman) also declined our fabrication request, citing the difficulty in working with a highly reactive Zr and Be. International fabrication options were explored in Europe and Asia, but this proved to be impractical, if not impossible. Consequently, experimental investigation of the Zr-Be binary system was dropped and exploration binary Zr-Y binary system was initiated. The motivation behind the Zr-Y system is the known thermodynamic stability of yttria over zirconia.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Point Kinetics and Reactivity Feedback Modeling in SAM

Over the past few years, the rapidly rising interest in advanced nuclear reactor technology has led to an increased need for the developments and applications of advanced computational tools for modeling and simulation. System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses [1]. It utilizes the object-oriented application framework MOOSE [2] to leverage the modern software environment and advanced numerical methods [3]. To meet this need, the capabilities of SAM are being extended to enable the transient modeling, analysis, and design of advanced nuclear reactor systems. The objective of this summary is to present the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. This summary also presents the new capability for modeling the thermal expansion reactivity feedback by coupling SAM and an external thermomechanics module (Tensor Mechanics) from MOOSE.

Hu, Guojun↗
DOE OSTI2014

MO-PIS-Exhibit Hall-01: Imaging: CT Dose Optimization Technologies I

Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The imaging topic this year is CT scanner dose optimization capabilities. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Dose Optimization Capabilities of GE Computed Tomography Scanners Presentation Time: 11:15 – 11:45 AM GE Healthcare is dedicated to the delivery of high quality clinical images through the development of technologies, which optimize the application of ionizing radiation. In computed tomography, dose management solutions fall into four categories: employs projection data and statistical modeling to decrease noise in the reconstructed image - creating an opportunity for mA reduction in the acquisition of diagnostic images. Veo represents true Model Based Iterative Reconstruction (MBiR). Using high-level algorithms in tandem with advanced computing power, Veo enables lower pixel noise standard deviation and improved spatial resolution within a single image. Advanced Adaptive Image Filters allow for maintenance of spatial resolution while reducing image noise. Examples of adaptive image space filters include Neuro 3-D filters and Cardiac Noise Reduction Filters. AutomA adjusts mA along the z-axis and is the CT equivalent of auto exposure control in conventional x-ray systems. Dynamic Z-axis Tracking offers an additional opportunity for dose reduction in helical acquisitions while SmartTrack Z-axis Tracking serves to ensure beam, collimator and detector alignment during tube rotation. SmartmA provides angular mA modulation. ECG Helical Modulation reduces mA during the systolic phase of the heart cycle. SmartBeam optimization uses bowtie beam-shaping hardware and software to filter off-axis x-rays - minimizing dose and reducing x-ray scatter. The DICOM Radiation Dose Structured Report (RDSR) generates a dose report at the conclusion of every examination. Dose Check preemptively notifies CT operators when scan parameters exceed user-defined dose thresholds. DoseWatch is an information technology application providing vendor-agnostic dose tracking and analysis for CT (and all other diagnostic x-ray modalities) SnapShot Pulse improves coronary CTA dose management. VolumeShuttle uses two acquisitions to increase coverage, decrease dose, and conserve on contrast administration. Color-Coding for Kids applies the Broselow-Luten Pediatric System to facilitate pediatric emergency care and reduce medical errors. FeatherLight achieves dose optimization through pediatric procedure-based protocols. Adventure Series scanners provide a child-friendly imaging environment promoting patient cooperation with resultant reduction in retakes and patient motion. Philips CT Dose Optimization Tools and Advanced Reconstruction Presentation Time: 11:45 ‘ 12:15 PM The first part of the talk will cover “Dose Reduction and Dose Optimization Technologies” present in Philips CT Scanners. The main Technologies to be presented include: DoseRight and tube current modulation (DoseRight, Z-DOM, 3D-DOM, DoseRight Cardiac) Special acquisition modes Beam filtration and beam shapers Eclipse collimator and ClearRay collimator NanoPanel detector DoseRight will cover automatic tube current selection that automatically adjusts the dose for the individual patient. The presentation will explore the modulation techniques currently employed in Philips CT scanners and will include the algorithmic concepts as well as illustrative examples. Modulation and current selection technologies to be covered include the Automatic Current Selection component of DoseRight, ZDOM longitudinal dose modulation, 3D-DOM (combination of longitudinal and rotational dose modulation), Cardiac Dose right (an ECG based dose modulation scheme), and the DoseRight Index (DRI) IQ index. The special acquisition modes covers acquisition techniques such as prospective gating that is designed to reduce exposure to the patient through the Cardiac Step and Shoot scan mode. This mode can substitute the much higher dose retrospective scan modes for certain types of cardiac imaging. The beam filtration and beam shaper portion will discuss the variety of filtration and beam shaping configurations available on Philips scanners. This topic includes the x-ray beam characteristics, tube filtration as well as dose compensator characteristics. The Eclipse collimator, ClearRay collimator and the NanoPanel detector portion will discuss additional technologies specific to wide coverage CT that address some of the unique challenges encountered and techniques employed to optimize image quality and optimize dose utilization. The Eclipse collimator reduces extraneous exposure by actively blocking the radiation tails at either end of helical scans that do not contribute to the image generation. The ClearRay collimator and the NanoPanel detector optimize the quality of the signal that reaches the detectors by addressing the increased scattered radiation present in wide coverage and the NanoPanel detector adds superior electronic noise characteristics valuable when imaging at a low dose level. The second part of the talk will present “Advanced Reconstruction Technologies” currently available on Philips CT Scanners. The talk will cover filtered back projection (FBP), iDose4 and Iterative Model Reconstruction (IMR). Each reconstruction method will include a discussion of the algorithm as well as similarities and differences between the algorithms. Examples illustrating the merits of each algorithm will be presented, and techniques and metrics to characterize the performance of each type of algorithm will be presented. The Filtered Back projection portion will discuss and provide a brief summary of relevant standard image reconstruction techniques in common use, and discuss the common tradeoffs when using the FBP algorithm. The iDose4 portion will present the algorithms used for iDose4 as well the different levels. The meaning of different levels of iDose4 available will be presented and quantified. Guidelines for selection iDose4 parameters based on the imaging need will be explained. The different image quality goals available with iDose4 and specifically how iDose4 enables noise reduction, spatial resolution improvement or both will be explained. The approaches to leveraging the benefits of iDose4 such as improved spatial resolution, decreased noise, and artifact prevention will be described and quantified; and measurements and metrics behind the improvements will be presented. The image quality benefits in specific imaging situations as well as how to best combine the technology with other dose reduction strategies to ensure the best image quality at a given dose level will be presented. Insight into the IMR algorithm as well as contrast to the iDose4 techniques and performance characteristics will be discussed. Metrics and techniques for characterizing this class of algorithm and IQ performance will be presented. The image quality benefits and the dose reduction capabilities of IMR will be explored. Illustrative examples of the noise reduction, spatial resolution improvement, and low contrast detectability improvements of the reconstruction method will be presented: clinical cases and phantom measurements demonstrating the benefits of IMR in the areas of low dose imaging, spatial resolution and low contrast resolution are discussed and the technical details behind the measurements will be presented compared to both iDose4 and traditional filtered back projection (FBP)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Computational Design of Advanced Nuclear Fuels

The objective of the project was to develop a method for theoretical understanding of nuclear fuel materials whose physical and thermophysical properties can be predicted from first principles using a novel dynamical mean field method for electronic structure calculations. We concentrated our study on uranium, plutonium, their oxides, nitrides, carbides, as well as some rare earth materials whose 4f eletrons provide a simplified framework for understanding complex behavior of the f electrons. We addressed the issues connected to the electronic structure, lattice instabilities, phonon and magnon dynamics as well as thermal conductivity. This allowed us to evaluate characteristics of advanced nuclear fuel systems using computer based simulations and avoid costly experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Optimization and large scale computation of an entropy-based moment closure

We present computational advances and results in the implementation of an entropy-based moment closure, M N , in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as P N , but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. Lastly, these results show, in particular, load balancing issues in scaling the M N algorithm that do not appear for the P N algorithm. We also observe that in weak scaling tests, the ratio in time to solution of M N to P N decreases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

ALD-Derived WO 3– x Leads to Nearly Wake-Up-Free Ferroelectric Hf 0.5 Zr 0.5 O 2 at Elevated Temperatures

Breaking the memory wall in advanced computing architectures will require complex 3D integration of emerging memory materials such as ferroelectrics─either within the back-end-of-line (BEOL) of CMOS front-end processes or through advanced 3D packaging technologies. Achieving this integration demands that memory materials exhibit high thermal resilience, with the capability to operate reliably at elevated temperatures, such as 125°C, due to the substantial heat generated by front-end transistors. However, silicon-compatible HfO 2 -based ferroelectrics tend to exhibit antiferroelectric-like behavior in this temperature range, accompanied by a more pronounced wake-up effect, posing significant challenges to their thermal reliability. Here, we report that by introducing a thin tungsten oxide (WO 3–x ) layer─known as an oxygen reservoir─and carefully tuning its oxygen content, ultrathin Hf 0.5 Zr 0.5 O 2 (5 nm) films can be made robust against the ferroelectric-to-antiferroelectric transition at elevated temperatures. This approach not only minimizes polarization loss in the pristine state but also effectively suppresses the wake-up effect, reducing the required wake-up cycles from 10 5 to only 10 at 125°C, a qualifying temperature for back-end memory integrated with front-end logic, as defined by the JEDEC standard. First-principles density functional theory (DFT) calculations reveal that WO 3 enhances the stability of the ferroelectric orthorhombic phase (o-phase) at elevated temperatures by increasing the tetragonal-to-orthorhombic phase energy gap and promoting favorable phonon mode evolution, thereby supporting o-phase formation under both thermodynamic and kinetic constraints.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Exascale computing and big data

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates the openness of the scientific process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics: A DOE-NIH Joint Workshop Executive Summary

The DOE-NIH Joint Workshop on Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics, held on September 27, 2024, brought together experts from government, academia, and industry to address critical challenges in radionuclide production and clinical translation. Here, the workshop emphasized interdisciplinary collaboration, particularly between the Department of Energy (DOE) and the National Institutes of Health (NIH), to strengthen the domestic isotope supply, streamline regulatory pathways, and further integrate computational tools into radiopharmaceutical therapy (RPT). Key discussions explored the role of AI-driven modeling, machine learning, and digital twin technologies in optimizing dosimetry, dynamically personalizing treatments, and reducing time to clinical adoption. Advances in predictive computational modeling were highlighted as essential for improving radionuclide yield, purity, and synthesis efficiency. Regulatory considerations and equitable access were central themes, with participants advocating for harmonized global standards, adaptive trial designs, and expanded infrastructure for clinical implementation. DOE computational and production infrastructure was emphasized. Future priorities identified include increased investment in radionuclide production infrastructure, expanded workforce development in radiopharmaceutical sciences and computational modeling, and the creation of robust public-private partnerships. The workshop concluded that continued strategic collaboration and sustained resources will be vital for advancing next-generation radiotheranostics, ensuring safe and effective therapies accessible to all patients.

digital twins↗
DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Sustain

Current building energy simulation technology requires excessive labor, time and expertise to create building energy models, excessive computational time for accurate simulations and difficulties with the interpretation of the results. These deficiencies can be ameliorated using modern graphical user interfaces and algorithms which take advantage of modern computer architectures and display capabilities. To prove this hypothesis, we developed an experimental test bed for building energy simulation. This novel test bed environment offers an easy-to-use interactive graphical interface, provides access to innovative simulation modules that run at accelerated computational speeds, and presents new graphics visualization methods to interpret simulation results. Our system offers the promise of dramatic ease of use in comparison with currently available building energy simulation tools. Its modular structure makes it suitable for early stage building design, as a research platform for the investigation of new simulation methods, and as a tool for teaching concepts of sustainable design. Improvements in the accuracy and execution speed of many of the simulation modules are based on the modification of advanced computer graphics rendering algorithms. Significant performance improvements are demonstrated in several computationally expensive energy simulation modules. The incorporation of these modern graphical techniques should advance the state of the art in the domain of whole building energy analysis and building performance simulation, particularly at the conceptual design stage when decisions have the greatest impact. More importantly, these better simulation tools will enable the transition from prescriptive to performative energy codes, resulting in better, more efficient designs for our future built environment.

Source record↗
DOE OSTI2012

A scalable messaging system for accelerating discovery from large scale scientific simulations

Emerging scientific and engineering simulations running at scale on leadership-class High End Computing (HEC) environments are producing large volumes of data, which has to be transported and analyzed before any insights can result from these simulations. The complexity and cost (in terms of time and energy) associated with managing and analyzing this data have become significant challenges, and are limiting the impact of these simulations. Recently, data-staging approaches along with in-situ and in-transit analytics have been proposed to address these challenges by offloading I/O and/or moving data processing closer to the data. However, scientists continue to be overwhelmed by the large data volumes and data rates. In this paper we address this latter challenge. Specifically, we propose a highly scalable and low-overhead associative messaging framework that runs on the data staging resources within the HEC platform, and builds on the staging-based online in-situ/in- transit analytics to provide publish/subscribe/notification-type messaging patterns to the scientist. Rather than having to ingest and inspect the data volumes, this messaging system allows scientists to (1) dynamically subscribe to data events of interest, e.g., simple data values or a complex function or simple reduction (max()/min()/avg()) of the data values in a certain region of the application domain is greater/less than a threshold value, or certain spatial/temporal data features or data patterns are detected; (2) define customized in-situ/in-transit actions that are triggered based on the events, such as data visualization or transformation; and (3) get notified when these events occur. The key contribution of this paper is a design and implementation that can support such a messaging abstraction at scale on high- end computing (HEC) systems with minimal overheads. We have implemented and deployed the messaging system on the Jaguar Cray XK6 machines at Oak Ridge National Laboratory and the Lonestar system at the Texas Advanced Computing Center (TACC), and we present the experimental performance evaluation using these HEC platforms in the paper.

Jin, Tong↗
DOE OSTI2015

The Science Training Program for Young Italian Physicists and Engineers at Fermilab

Since 1984 Fermilab has been hosting a two-month summer training program for selected undergraduate and graduate Italian students in physics and engineering. Building on the traditional close collaboration between the Italian National Institute of Nuclear Physics (INFN) and Fermilab, the program is supported by INFN, by the DOE and by the Scuola Superiore di Sant`Anna of Pisa (SSSA), and is run by the Cultural Association of Italians at Fermilab (CAIF). This year the University of Pisa has qualified it as a “University of Pisa Summer School”, and will grant successful students with European Supplementary Credits. Physics students join the Fermilab HEP research groups, while engineers join the Particle Physics, Accelerator, Technical, and Computing Divisions. Some students have also been sent to other U.S. laboratories and universities for special trainings. The programs cover topics of great interest for science and for social applications in general, like advanced computing, distributed data analysis, nanoelectronics, particle detectors for earth and space experiments, high precision mechanics, applied superconductivity. In the years, over 350 students have been trained and are now employed in the most diverse fields in Italy, Europe, and the U.S. In addition, the existing Laurea Program in Fermilab Technical Division was extended to the whole laboratory, with presently two students in Master’s thesis programs on neutrino physics and detectors in the Neutrino Division. And finally, a joint venture with the Italian Scientists and Scholars North-America Foundation (ISSNAF) provided this year 4 professional engineers free of charge for Fermilab. More details on all of the above can be found below.

Barzi, Emanuela↗
DOE OSTI2022

Study of recirculating liquid fuel in a 1D critical stationary system

Several studies have been conducted to investigate the physics of liquid fuel reactors, showing also applications with molten salts. A liquid nuclear fuel implies changes in the neutron balance equation to take into account the precursors' displacement and the emission of delayed neutrons in a different position than at the original fission. This requires to upgrade the computer codes normally used to calculate nuclear reactors using only solid fuel. In this work, we revisit a simple problem with liquid fuel, which is proposed for the verification of the numerical solutions obtained by advanced computer codes. This problem studies criticality with constant coefficients, thus neglecting thermal feedback. We elaborate on the analytical solution of the problem, deriving also a generalized eigenvalue problem by finite-volume integration over the cells of a discretized mesh to study the evolution of the dominance ratio with fuel velocity. Finally, we investigate the influence of the fuel velocity on the reactivity of the system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Gary Laughlin IHNS Intro to 2015 HPC Annual Report

The International, Homeland, and Nuclear Security (IHNS) Program Management Unit (PMU) oversees a broad portfolio of Sandia’s programs in areas ranging from global nuclear security to critical asset protection. We use science and technology, innovative research, and global engagement to counter threats, reduce dangers, and respond to disasters. The PMU draws on the skills of scientists and engineers from across Sandia. Our programs focus on protecting US government installations, safeguarding nuclear weapons and materials, facilitating nonproliferation activities, securing infrastructures, countering chemical and biological dangers, and reducing the risk of terrorist threats. We conduct research in risk and threat analysis, monitoring and detection, decontamination and recovery, and situational awareness. We develop technologies for verifying arms control agreements, neutralizing dangerous materials, detecting intruders, and strengthening resiliency. Our programs use Sandia’s High-Performance Computing resources for predictive modeling and simulation of interdependent systems, for modeling dynamic threats and forecasting adaptive behavior, and for enabling decision support and processing large cyber data streams. In this report, we highlight four advanced computation projects that illustrate the breadth of the IHNS mission space.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Vehicle Lateral Offset Estimation Using Infrastructure Information for Reduced Compute Load

Accurate perception of the driving environment and a highly accurate position of the vehicle are paramount to safe Autonomous Vehicle (AV) operation. AVs gather data about the environment using various sensors. For a robust perception and localization system, incoming data from multiple sensors is usually fused together using advanced computational algorithms, which historically requires a high-compute load. To reduce AV compute load and its negative effects on vehicle energy efficiency, we propose a new infrastructure information source (IIS) to provide environmental data to the AV. The new energy–efficient IIS, chip–enabled raised pavement markers are mounted along road lane lines and are able to communicate a unique identifier and their global navigation satellite system position to the AV. This new IIS is incorporated into an energy efficient sensor fusion strategy that combines its information with that from traditional sensor. IIS reduce the need for camera imaging, image processing, and LIDAR use and point cloud processing. We show that IIS, when combined with traditional sensors, results in more accurate perception and localization outcomes and a reduced AV compute load.

Sharma, Sachin↗
DOE OSTI2022

Dielectric screening and vacancy formation for large neutral and charged Si n H m ( n > 1500 ) nanocrystals using real-space pseudopotentials

A commonly used procedure for computing the properties of defects in crystalline materials is to consider a large supercell that includes the defect of interest. This is a straightforward technique as standard energy band codes can be used for such computations. For neutral defects, the only impediment of such an approach is to avoid defect-defect interactions between adjoining cells. However, this procedure can be complex if the defect of interest is charged as the system at large contains Coulombic divergences. Moreover, some have recently argued that the conventional definition of formation energies for charged defects cannot be reconciled with statistical mechanics. Here, we focus on an alternative approach. We consider large nanocrystals wherein a charged defect can be placed. Since the system is confined, a charged defect within the nanocrystal does not result in a Coulombic divergence. The chief impediment is computational, i.e., while no defect-defect or Coulombic divergences are present, the nanocrystal must be sufficiently large to allow the system to properly replicate a bulklike configuration. With the development of new algorithms and hardware advances, computations for systems of sufficient size to address this issue are feasible. In particular, we solve the Kohn-Sham equation in real space using pseudopotential-density-functional theory for large silicon nanocrystals, which contain thousands of atoms. Further, we focus on (i) the screening of a point charge and (ii) the formation of a charged vacancy in hydrogen-terminated silicon nanocrystals. This approach allows us to examine the role of quantum confinement in addition to exploring the bulk limit. Comparisons to other methods confirm the viability of this approach.

36 MATERIALS SCIENCE↗