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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, Implementation Strategy for a Distribution Management System

Electric distribution utilities encounter many challenges to successful deployment of Distribution Management Systems (DMSs). The key challenges are documented in this report, along with suggestions for overcoming them. This report offers a recommended list of activities for implementing a DMS. It takes a strategic approach to implementing DMS from a project management perspective. The project management strategy covers DMS planning, procurement, design, building, testing, Installation, commissioning, and system integration issues and solutions. It identifies the risks that are associated with implementation and suggests strategies for utilities to use to mitigate them or avoid them altogether. Attention is given to common barriers to successful DMS implementation. This report begins with an overview of the implementation strategy for a DMS and proceeds to put forward a basic approach for procuring hardware and software for a DMS; designing the interfaces with external corporate computing systems such as EMS, GIS, OMS, and AMI; and implementing a complete solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cybersecurity Assessment Methodology for International Safeguards

International nuclear safeguards are technical measures implemented by the International Atomic Energy Agency (IAEA) to verify the correctness and completeness of declarations made by States about their nuclear activities. The systems used to verify such activities include electronic and digital hardware and software components capable of data collection, processing, analysis, storage and transmission. Despite increasing efforts to protect digital systems against unauthorized access or attack through cybersecurity measures, these systems are not immune to cyber exploitation that could compromise their integrity or reliability. Previous versions of these systems did not include capabilities that exist today, such as BluetoothTM and GPS. The inclusion of these new capabilities, as well as new data processing and storage mechanisms, adds new attack vectors and opportunities for adversaries to exploit the devices that did not previously exist. As mentioned in the above referenced Cybersecurity for Safeguards study, cyber-domain vulnerabilities present risks to the equipment used to perform the international nuclear safeguards mission. The IAEA has produced guidance on the protection of nuclear facilities and their computer systems against cyber threats, but these documents do not specifically address the risks to safeguards or safeguards equipment. In response, the U.S. Department of Energy National Nuclear Security Administration (DOE/NNSA) Office of International Nuclear Safeguards/Safeguards Technology Development (NA-241) sponsored Sandia National Laboratories (Sandia, SNL) and the Idaho National Laboratory (Idaho, INL) to conduct a one-year study to evaluate cyber related vulnerabilities in safeguards equipment and develop recommendations for the mitigation of any identified risks.

97 MATHEMATICS AND COMPUTING↗

The Trinity Center of Excellence Co-Design Best Practices

Co-design between application developers and the vendors providing high-performance computing systems is essential to efficiently using current-generation HPC systems and shaping next-generation architectures. Application developers are faced with the challenge of effectively orchestrating many hardware threads and exploiting vector instructions, which can require code modifications. Will refactoring applications for current-generation systems apply to future-generation systems? Is there help available for this enormous task? Over the past 10 years, a partnership has evolved to address these issues. Centers of Excellence are mutually beneficial collaborations between application developers and vendors; vendors receive a better understanding of the needs of their users, and users receive a better understanding of the characteristics of the hardware, system software, and tools available to address their challenges. Lastly, this article describes the partnership between two vendors, Cray and Intel, and the application teams working together in the Trinity Center of Excellence.

97 MATHEMATICS AND COMPUTING↗

Thermodynamic properties and phase stability of the Ba-Bi system: A combined computational and experimental study

The thermodynamic properties and phase stability of the Ba-Bi system are investigated computationally and experimentally in the present work. The enthalpies of formation and the finite temperature thermodynamic properties of seven compounds are predicted by first-principles calculations based on density functional theory (DFT), indicating five compounds (BaBi 3 , Ba 11 Bi 10 , Ba 4 Bi 3 , Ba 5 Bi 3 , and Ba 2 Bi) to be stable. Phase relations at 773 K and 858 K with composition x Ba = 0.90 are established by isothermal annealing and powder X-ray diffraction (XRD) to clarify the previously observed phase transition at 796 K. The extremely low chemical activity of Ba in liquid for a wide range of temperatures and compositions indicates very strong short-range ordering in the liquid phase which is modeled in the present work by introducing the Ba 4 Bi 3 and BaBi 3 associates in the liquid phase. Both thermodynamic and phase equilibrium data are then used to evaluate the model parameters in Gibbs energy functions of the five stable compounds and three solution phases of liquid, bcc, and rhombohedral phases by the CALPHAD (CALculation of PHAse Diagram) technique. Here the present work shows that the Ba-Bi system consists of three eutectic reactions, two peritectic reactions, one peritectoid reaction, and two congruent reactions, as well as that the concentrations of associates are very high in the liquid phase with very low concentration of atomic Ba, which provides the fundamental understanding as to why Bi can be used to remove Ba ions from molten salt solutions.

36 MATERIALS SCIENCE↗

System and method for optimizing hydrocarbon production from subsurface reservoirs

A method is described for subsurface hydrocarbon reservoir characterization including receiving a time-lapse electromagnetic (EM) dataset and a flow dataset; inverting the time-lapse EM dataset using a parametric inversion that models steel well casings to determine a volume of fluid-changed reservoir; inverting the time-lapse EM dataset and the flow dataset using a joint inversion that honors the volume of the fluid-changed reservoir to determine relative permeability and capillary pressure; and characterizing flow characteristics in the volume of the fluid-changed reservoir. The method may be executed by a computer system.

Hoversten, Gary Michael↗

System and method for the direct calorimetric measurement of laser absorptivity of materials

A method and system for calorimetrically measuring the temperature-dependent absorptivity of a homogeneous material dimensioned to be thin and flat with a predetermined uniform thickness and a predetermined porosity. The system includes a material holder adapted to support and thermally isolate the material to be measured, an irradiation source adapted to uniformly irradiate the material with a beam of electromagnetic radiation, and an irradiation source controller adapted to control the irradiation source to uniformly heat the material during a heating period, followed by a cooling period when the material is not irradiated. A thermal sensor measures temperature of the material during the heating and cooling periods, and a computing system first calculates temperature-dependent convective and radiative thermal losses of the material based on the measured temperature of the material during the cooling period when beam intensity is zero, followed by calculation of the temperature-dependent absorptivity of the material based on the temperature-dependent convective and radiative thermal losses determined from the cooling period.

Rubenchik, Alexander↗

Best-Estimate-Plus-Uncertainty-Informed Deterministic Safety Evaluation

Nuclear power plant (NPP) utilities operate contingent on receiving a favorable safety assessment from their national regulatory and safety authority. Among the many facets of NPP safety addressed is verification of integral design-basis performance - a demonstration of a plant's response to a suite of challenging transient and accident scenarios. Thermal-hydraulic system computer codes like RELAP5, TRAC, CATHARE, and ATHLET are used as the simulation engine as part of a broader evaluation model that accounts for a variety of uncertainties. It is common for these evaluation models to apply either a super-bounding/ deterministic or best-estimate plus uncertainty (BEPU) approach. The trend over the past two decades has been away from the classical deterministic methods towards methods explicitly incorporating parametric uncertainty models. These methods center upon the evaluation of parametric and system response uncertainties, where these uncertainties are derived from the convolution of one or more parametric uncertainty models. Acceptance of BEPU methods has provided the nuclear industry benefits regarding operational flexibility and, in some cases, power output. The advantage of BEPU for new NPPs is less obvious. Generally, these new designs include engineered safety features that practically eliminate fuel damage resulting from design-basis events. To substantiate such claims, applying super-bounding assumptions on uncertainties may be a more expedient demonstration of a plant's safety case than those based on BEPU. In addition, the requirements on design inputs for a deterministic evaluation model are substantially less than that for a BEPU evaluation model. As such, applying a deterministic evaluation model is expected to have the advantage of reducing the duration of the licensing review process. For the current operating fleet of light-water reactors (LWRs), the nuclear safety authorities in most countries have followed the U.S. Nuclear Regulatory Commission's rules for the preparation of safety analysis. These rules are specified in the U.S. Code of Federal Regulations, most notably in, Part 10, Section 50.46, entitled 'acceptance criteria for emergency core cooling systems for light-water nuclear power reactors' and its Appendix K. Notably, Appendix K specifies deterministic requirements for analysis of the loss-of-coolant accident (LOCA), which is generally regarded as the maximum credible accident for LWRs. Projecting 10 CFR 50, Appendix K, to new plants is not obviously applicable as it addresses light water fluid flow and heat transfer phenomena associated with core uncovery. Preventing core uncovery is a requirement for several designs in the class of small modular reactors (SMR). In doing so, the majority of phenomenological uncertainties prescribed in Appendix K are eliminated. Similarly, the impact of other phenomena to effect a change in various safety measures, i.e., figures-of-merit, is expected to be different. The implication is that development of a deterministic evaluation model must be derived with an original technical basis rather than solely rely on Appendix K. While a logical conclusion, the expectation of original bases, regardless of the treatment of uncertainties, is embodied in the U.S. NRC's Regulatory Guide (RG) 1.203, Transient and Accident Analysis. Within the evaluation model development and application process framework of RG 1.203, this paper describes a BEPU-informed deterministic evaluation model for NPPs with large inherent safety margins. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Rolex: Resilience-oriented language extensions for extreme-scale systems

Future exascale high-performance computing (HPC) systems will be constructed from VLSI devices that will be less reliable than those used today, and faults will become the norm, not the exception. This will pose significant problems for system designers and programmers, who for half-a-century have enjoyed an execution model that assumed correct behavior by the underlying computing system. The mean time to failure (MTTF) of the system scales inversely to the number of components in the system and therefore faults and resultant system level failures will increase, as systems scale in terms of the number of processor cores and memory modules used. However every error detected need not cause catastrophic failure. Many HPC applications are inherently fault resilient. Yet it is the application programmers who have this knowledge but lack mechanisms to convey it to the system. In this paper, we present new Resilience Oriented Language Extensions (Rolex) which facilitate the incorporation of fault resilience as an intrinsic property of the application code. We describe the syntax and semantics of the language extensions as well as the implementation of the supporting compiler infrastructure and runtime system. Furthermore, our experiments show that an approach that leverages the programmer's insight to reason about the context and significance of faults to the application outcome significantly improves the probability that an application runs to a successful conclusion.

97 MATHEMATICS AND COMPUTING↗

DragonView: Toward Understanding Network Interference in Dragonfly-based Supercomputers

Acquiring and maintaining high performance computing systems represents a substantial, long term investment. Therefore, it is paramount to optimize their utilization in order to maximize the return on investment and the impact on science and engineering. In this context, network congestion and inter-job interference are a major challenge as they can lead to significant systemwide performance degregation. This is especially pertinent in shared interconnects such as the dragonfly network, in which resources are shared by multiple jobs. Since many large-scale applications are communication-bound, a few communication heavy applications can have a large impact on the performance of all jobs and decrease the overall system throughput. In this paper, we describe a web-based visual analytics environment to study congestion and inter-job interference on dragonfly networks. The system enables network architects, system administrators and application developers to explore the potential impact of machine configuration, job placement policies and routing algorithms by visualizing and comparing ensembles of simulated workloads and real world data. We focus on the design of the system and describe the challenges, design decisions and the final implementation. Finally, we present two detailed case studies of prototypical analysis sessions by our stakeholders aimed at exploring the implications of different workloads and machine configurations using ensembles of network simulations.

97 MATHEMATICS AND COMPUTING↗

Massive Asynchronous Parallelization of Sparse Matrix Factorizations

Solving sparse problems is at the core of many DOE computational science applications. We focus on the challenge of developing sparse algorithms that can fully exploit the parallelism in extreme-scale computing systems, in particular systems with massive numbers of cores per node. Our approach is to express a sparse matrix factorization as a large number of bilinear constraint equations, and then solving these equations via an asynchronous iterative method. The unknowns in these equations are the matrix entries of the factorization that is desired.

97 MATHEMATICS AND COMPUTING↗

Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications

With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage integrated CPU-GPU power management on architectures like the NVIDIA GH200 superchip. We evaluate energy-performance metrics that account for simultaneous CPU and GPU power-capping effects by using two complementary approaches: speedup-energy-delay and a Euclidean distance-based multi-objective optimization method. By targeting a mostly compute-bound exascale science application, the Locally Self-Consistent Multiple Scattering (LSMS), we explore challenging scenarios to identify potential opportunities for energy savings in exascale applications, and we recognize that even modest reductions in energy consumption can have significant overall impacts. Our results highlight how GPU task-specific dynamic power-cap adjustments combined with integrated CPU-GPU power steering can improve the energy utilization of certain GPU tasks, thereby laying the groundwork for future adaptive optimization strategies.

Patrou, Maria [ORNL] (ORCID:0000000339754638)↗

QuComm: Optimizing Collective Communication for Distributed Quantum Computing

Distributed quantum computing (DQC) is a scalable way to build a large-scale quantum computing system while the error-prone nonlocal communication between DQC nodes may heavily degrade the fidelity of the distributed quantum program and thus demands specific compiler optimizations. Previous compilers on DQC communication optimization either assumes unlimited communication resource or a few communication qubits due to the hardware limitation. The former compilers may not be efficient when interfacing with communication-resource-constrained DQC hardware while the latter compilers lose the opportunities of optimizing collective communication and routing concurrent communication as they unnecessarily couple limited communication qubits with the implementation of expensive inter-node operations. In this paper, we invent the communication buffer, a communication facility consisting of idle qubits in each compute node, to decouple the execution of inter-node quantum operations from communication qubits: communication qubits are devoted to generating inter-node entanglement while internode operations are conducted in the communication buffer. The communication buffer provides an intermediate layer for inter-node communication and paves the way for collective communication optimization. We then propose QuComm, a buffer-based compiler framework that first performs smart buffer allocation according to communication characteristics of the distributed quantum program and then optimizes and collectively routes inter-node quantum operations. Experimental results on a hierarchical DQC system show that the proposed QuComm can reduce the most expensive inter-node communication request and the latency of various distributed quantum programs by 50.4% and 47.6% on average, respectively.

Wu, Anbang↗

Optical N-plasmon: topological hydrodynamic excitations in graphene from repulsive Hall viscosity

Abstract Edge states occurring in Chern and quantum spin-Hall phases are signatures of the topological electronic band structure in two-dimensional (2D) materials. Recently, a new topological electromagnetic phase of graphene characterized by the optical N-invariant was proposed. Optical N-invariant arises from repulsive Hall viscosity in hydrodynamic many-body electron systems, distinct from the Chern and Z 2 invariants. In this paper, we introduce the topologically protected edge excitation—optical N-plasmon of interacting many-body electron systems in the topological optical N-phase. These optical N-plasmons are signatures of the topological plasmonic band structure in 2D materials. We demonstrate that optical N-plasmons exhibit unique dispersion relations, stability against various boundary conditions, and edge profiles when compared with the topologically trivial edge magneto plasmons. Based on the optical N-plasmon, we design an ultra sub-wavelength broadband topological hydrodynamic circulator, which is a chiral quantum radio-frequency circuit component crucial for information routing and interfacing quantum–classical computing systems. Furthermore, we reveal that optical N-plasmons can be effectively tuned by the neighboring dielectric environment without breaking the topological properties. Our work provides a smoking gun signature of topological electromagnetic phases occurring in 2D materials arising from repulsive Hall viscosity.

Physics↗

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗

Design Installation and Operation of the Vortex ART Platform

ATS platforms are some of the largest, most complex, and most expensive computer systems installed in the United States at just a few major national laboratories. This milestone describes our recent efforts to procure, install, and test a machine called Vortex at Sandia National Laboratories that is compatible with the larger ATS platform Sierra at LLNL. In this milestone, we have 1) configured and procured a machine with similar hardware characteristics as Sierra ATS, 2) installed the machine, verified its physical hardware, and measured its baseline performance, and 3) demonstrated the machine's compatibility with Sierra ATS, and capacity for useful development and testing of Sandia computer codes (such as SPARC), including uses such as nightly regression testing workloads.

97 MATHEMATICS AND COMPUTING↗

Automated Reaction Kinetics of Gas-Phase Organic Species over Multiwell Potential Energy Surfaces

Automation of rate-coefficient calculations for gas-phase organic species became possible in recent years and has transformed how we explore these complicated systems computationally. Kinetics workflow tools bring rigor and speed and eliminate a large fraction of manual labor and related error sources. In this paper we give an overview of this quickly evolving field and illustrate, through five detailed examples, the capabilities of our own automated tool, KinBot. Here we bring examples from combustion and atmospheric chemistry of C-, H-, O-, and N-atom-containing species that are relevant to molecular weight growth and autoxidation processes. The examples shed light on the capabilities of automation and also highlight particular challenges associated with the various chemical systems that need to be addressed in future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗