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DOE OSTI2022

Modeling Methods for Capturing System Interactions of Combined Technologies: A Study of PV + Battery

The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid at higher penetrations. Additionally, as battery costs decline it becomes important to understand the benefits and limitations of battery storage for the grid as well as potential benefits of co-locating battery storage and PV, particularly within the realm of future system planning. However, it is non-trivial to capture these potential benefits within a linearized capacity expansion model (CEM). This paper presents methodological developments to more fully represent the value and limitations of coupled PV and battery systems (PV + Battery) in CEMs using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch in the Western Interconnection of North America through 2045. We use the model to simulate the evolution of the generation and transmission system under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and midline PV and battery cost projections. When incorporating PV + battery, we find that it is important for CEMs to capture the ability of the coupled technology to provide firm capacity and reduce expected curtailment, compared to independent systems. These interactions can have even more dramatic impacts at higher solar penetrations.

14 SOLAR ENERGY↗

DOE OSTI2025

Data Structure Alchemy

In an increasingly more data-driven world, the project set out to uncover the first principles of data-structure design, chart the immense design space they form, and build automation that can synthesize an optimal structure, or even a whole storage engine, for any given workload, hardware platform, and cost target. Data structures are at the center of every computational system and are directly responsible for its performance. Two core technical thrusts were defined: 1) Mapping design spaces for key data-centric abstractions (filters, hash functions, storage-engine layouts, neural-network topologies, blockchain protocols, image layouts, etc.). 2) Developing search & synthesis algorithms, initially analytical cost models, later neural-guided bi-level optimisers that navigate sextillions of candidate designs in seconds and materialise the best one as ready‐to-run code. This report distills the key insights, accomplishments, and impact.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Unlocking the Tight Oil Reservoirs of the Powder River Basin, Wyoming

The project focused on detailed geologic characterization, geomechanical studies, well completion optimization, stimulation monitoring, and field development strategies. A key aspect involved partnerships with industry and academic collaborators such as Occidental Petroleum, Southern Illinois University, Britt Rock Mechanics and Piri Technologies. Data acquisition included drilling, logging, coring, deployment of fiber optics, and microseismic monitoring. The project emphasized feedback loops for continuous model updating and integration of economic evaluations to guide development strategies.

02 PETROLEUM↗

DOE OSTI2012

Creating NDA working standards through high-fidelity spent fuel modeling

The Next Generation Safeguards Initiative (NGSI) is developing advanced non-destructive assay (NDA) techniques for spent nuclear fuel assemblies to advance the state-of-the-art in safeguards measurements. These measurements aim beyond the capabilities of existing methods to include the evaluation of plutonium and fissile material inventory, independent of operator declarations. Testing and evaluation of advanced NDA performance will require reference assemblies with well-characterized compositions to serve as working standards against which the NDA methods can be benchmarked and for uncertainty quantification. To support the development of standards for the NGSI spent fuel NDA project, high-fidelity modeling of irradiated fuel assemblies is being performed to characterize fuel compositions and radiation emission data. The assembly depletion simulations apply detailed operating history information and core simulation data as it is available to perform high fidelity axial and pin-by-pin fuel characterization for more than 1600 nuclides. The resulting pin-by-pin isotopic inventories are used to optimize the NDA measurements and provide information necessary to unfold and interpret the measurement data, e.g., passive gamma emitters, neutron emitters, neutron absorbers, and fissile content. A key requirement of this study is the analysis of uncertainties associated with the calculated compositions and signatures for the standard assemblies; uncertainties introduced by the calculation methods, nuclear data, and operating information. An integral part of this assessment involves the application of experimental data from destructive radiochemical assay to assess the uncertainty and bias in computed inventories, the impact of parameters such as assembly burnup gradients and burnable poisons, and the influence of neighboring assemblies on periphery rods. This paper will present the results of high fidelity assembly depletion modeling and uncertainty analysis from independent calculations performed using SCALE and MCNP. This work is supported by the Next Generation Safeguards Initiative, Office of Nuclear Safeguards and Security, National Nuclear Security Administration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Global Transformations for Legacy Parallel Applications via Structural Analysis and Rewriting

Performance and scalability optimization of large HPC applications is currently a labor-intensive, manual process with very low productivity. Major difficulties come from the disaggregated environment for HPC application development: the compiler is only involved in local decisions (core or multithreaded domain), while a library-based, communication-oriented programming model realizes whole-machine parallelism. Realizing any major global change in such a disaggregated environment is very difficult and involves changing large portions of the source code. We present semi-automated techniques, based on structural analysis and rewriting, for performing global transformations on an HPC application source code. We present two case studies using the Self-Consistent Field (SCF) standalone benchmark as well as the Coupled Cluster (CCSD) module (2.9 million lines of Fortran code), a key module of the NWChem computational chemistry application. We demonstrate how structural rewriting techniques can be used to automate transformations that affect multiple sections of the application's source code. We show that the transformations can be applied in a systematic fashion across the source code bases with minimal manual effort. These transformations improve the scalability of the SCF benchmark by more than two orders of magnitude and the performance of the full CCSD module by a factor of 4.0.

legacy parallel applications↗

DOE OSTI2024

Exploring Subsite Selectivity within Plasmodium vivax N -Myristoyltransferase Using Pyrazole-Derived Inhibitors

N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Evolution of the ROOT Tree I/O

The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

Analysis of surface integrity of grinded gears using Barkhausen noise analysis and x-ray diffraction

The contribution is focused to present results of study grinded gears made of 18CrNiMo7-6 steel used in the wind power plant for support (service) purposes. These gears were case-hardened due to standard hard case and soft core formation. This heat treatment increases wear resistance and fatigue strength of machine parts. During serial production some troubles with surface integrity have occurred. When solving complex problems lots of samples were prepared. For grinding of gears were used different parameters of cutting speed, number of material removal and lots from different subsuppliers. Material characterization was carried out using Barkhausen noise analysis (BNA) device; X-ray diffraction (XRD) measurement of surface residual stresses was done as well. Depth profile of measured characteristics, e.g. magnetoelastic parameter and residual stress was obtained by step by step layers' removing using electrolytic etching. BNA software Viewscan was used to measure magnetizing frequency sweep (MFS) and magnetizing voltage sweep (MVS). Scanning of Magnetoelastic parameter (MP) endwise individual teeth were also carried out with Viewscan. These measurements were done to find problematic surface areas after grinding such as thermal damaged locations. Plots of the hardness and thickness of case-hardened layer on cross sections were measurered as well. Evaluation of structure of subsurface case-hardened layer and core was made on etched metallographic patterns. The aim of performed measurements was to find correlation between conditions of grinding, residual stresses and structural and magnetoelastic parameters. Based on correlation of measured values and technological parameters optimizing the production of gears will be done.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System

Hardware and software co-design is becoming increasingly important due to complexities in supercomputing architectures. Simulating applications before there is access to the real hardware can assist machine architects in making better design decisions that can optimize application performance. At the same time, the application and runtime can be optimized and tuned beforehand. BigSim is a simulation-based performance prediction framework designed for these purposes. It can be used to perform packet-level network simulations of parallel applications using existing parallel machines. In this paper, we demonstrate the utility of BigSim in analyzing and optimizing parallel application performance for future systems based on the PERCS network. We present simulation studies using benchmarks and real applications expected to run on future supercomputers. Future petascale systems will have more than 100,000 cores, and we present simulations at that scale.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

The QCAD framework for quantum device modeling

We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly Si double quantum dots (DQDs) developed for quantum computing. The simulator core includes Poisson, Schrodinger, and Configuration Interaction solvers which can be run individually or combined self-consistently. The simulator is built upon Sandia-developed Trilinos and Albany components, and is interfaced with the Dakota optimization tool. It is being developed for seamless integration, high flexibility and throughput, and is intended to be open source. The QCAD tool has been used to simulate a large number of fabricated silicon DQDs and has provided fast feedback for design comparison and optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Ard [SWR-25-18]

A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations. Dig into wind farm design. An ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms. The problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest! Ard seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.

Frontin, Cory [National Renewable Energy Laborator↗

DOE OSTI2013

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|SpeedShop

In this project we created a community tool infrastructure for program development tools targeting Petascale class machines and beyond. This includes tools for performance analysis, debugging, and correctness tools, as well as tuning and optimization frameworks. The developed infrastructure provides a comprehensive and extensible set of individual tool building components. We started with the basic elements necessary across all tools in such an infrastructure followed by a set of generic core modules that allow a comprehensive performance analysis at scale. Further, we developed a methodology and workflow that allows others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In order to form the core modules, we built on the existing Open|SpeedShop infrastructure and decomposed it into individual modules that match the necessary tool components. At the same time, we addressed the challenges found in performance tools for petascale systems in each module. When assembled, this instantiation of community tool infrastructure provides an enhanced version of Open|SpeedShop, which, while completely different in its architecture, provides scalable performance analysis for petascale applications through a familiar interface. This project also built upon and enhances capabilities and reusability of project partner components as specified in the original project proposal. The overall project team’s work over the project funding cycle was focused on several areas of research, which are described in the following sections. The reminder of this report also highlights related work as well as preliminary work that supported the project. In addition to the project partners funded by the Office of Science under this grant, the project team included several collaborators who contribute to the overall design of the envisioned tool infrastructure. In particular, the project team worked closely with the other two DOE NNSA laboratories Los Alamos and Sandia leveraging co-funding for Krell by ASC’s Common Computing Environment (CCE) program as laid out in the original proposal. The ASC CCE co-funding, coordinated through LLNL, was for 50% of the total project funding, with the ASC CCE portion of the funding going entirely to Krell, while the ASCR funding itself was split between Krell and the funded partners. This report covers the entire project from both funding sources. Additionally, the team leveraged the expertise of software engineering researchers from Carnegie Mellon University, who specialize in software framework design, in order to achieve a broadly acceptable component framework. The Component Based Tool Framework (CBTF) software has been released to the community. Information related to the project and the released software can be found on the CBTF wiki page at: http://sourceforge.net/p/cbtf/wiki/Home.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Monitoring for Additive Manufacturing Technologies: Report on Progress, Achievements, and Limitations of Monitoring Techniques

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology of choice for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence that can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree data sets is vital, should these data be generated before, during, or after the manufacturing process. This report focuses on the collection of manufacturing process data using systems instrumentation and monitoring. It presents an inventory of the various monitoring modalities installed on the manufacturing systems by the machine manufacturer or specifically designed by our team to fill information gaps. It also provides details on other relevant data streams available and leverageable to evaluate the manufacturing process on all classes of AM systems investigated during the first year of this program. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

42 ENGINEERING↗

DOE OSTI2020

A Physical Model for Understanding the Activation of MoS 2 Basal-plane Sulfur Atoms for the Hydrogen Evolution Reaction

All the DFT calculations are done with the Vienna Ab Initio Simulation Package (VASP) using the projector augmented wave method. The Bayesian error estimation exchange-correlation functionals (BEEF) with van der Waals interactions are employed. A plane-wave cutoff energy of 400 eV is used together with PAW-PBE potentials where semi core p states are treated as valence. All the calculations allow for spin-polarization. The structures are relaxed until the force is converged to < 0.01 eV/Å. The lattice parameter of MoS 2 unit cell, optimized with this functional, is 3.19 Å. A (4×4) supercell is used to model all the transition metal doped MoS 2 systems studied here, including those with S vacancies. For calculations in the initial dopant structure exploration, the Brillouin zone is sampled with a 3x3x1 Monkhorst-Pack k-point mesh. A 6×6×1 Monkhorst-Pack k-point mesh is used for the H binding energy and density of states calculations. In all calculations, the vacuum layer is set as 15 Å to eliminate periodic interaction perpendicular to the basal plane.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2016

SPOC Benchmark Case: SNRE Model

The Small Nuclear Rocket Engine (SNRE) was modeled in the Center for Space Nuclear Research’s (CSNR) Space Propulsion Optimization Code (SPOC). SPOC aims to create nuclear thermal propulsion (NTP) geometries quickly to perform parametric studies on design spaces of historic and new NTP designs. The SNRE geometry was modeled in SPOC and a critical core with a reasonable amount of criticality margin was found. The fuel, tie-tubes, reflector, and control drum masses were predicted rather well. These are all very important for neutronics calculations so the active reactor geometries created with SPOC can continue to be trusted. Thermal calculations of the average and hot fuel channels agreed very well. The specific impulse calculations used historically and in SPOC disagree so mass flow rates and impulses differed. Modeling peripheral and power balance components that do not affect nuclear characteristics of the core is not a feature of SPOC and as such, these components should continue to be designed using other tools. A full paper detailing the available SNRE data and comparisons with SPOC outputs will be submitted as a follow-up to this abstract.

MCNP↗

DOE OSTI2015

Advanced instrumentation and analysis methods for in-pile thermal and nuclear measurements: from out-of-pile studies to irradiation campaigns

Research and development on nuclear fuel behavior under irradiations and accelerated ageing of structure materials is a key issue for sustainable nuclear energy in order to meet specific needs by keeping the best level of safety. A new Material Testing Reactor (MTR), the Jules Horowitz Reactor (JHR) currently under construction in the South of France in the CEA Cadarache research centre will offer a real opportunity to perform R and D programs and hence will crucially contribute to the selection, optimization and qualification of innovative materials and fuels. To perform such programs advanced accurate and innovative experiments, irradiation devices that contain material and fuel samples are required to be set up inside or beside the reactor core. These experiments needs beforehand in situ and on line sophisticated measurements to accurately reach specific and determining parameters such as thermal and fast neutron fluxes, nuclear heating and temperature conditions to precisely monitor and control the conducted assays. Consequently, since 2009 CEA and Aix-Marseille University collaborate in order to design and develop a new multi-sensor device which will be dedicated to measuring profiles of such conditions inside the experimental channels of the JHR. These works are performed in the framework of two complementary joint research programs called MAHRI-BETHY and INCORE. These programs couple experimental studies carried out both out-of nuclear fluxes (in laboratory) and under irradiation conditions (in OSIRIS MTR reactor in France and MARIA MTR reactor in Poland) with numerical works realized by thermal simulations (CAST3M code) and Monte Carlo simulations (MCNP code). These programs deal with three main aims. The first one corresponds to the design and/or the test of new in-pile instrumentation. The second one concerns the development of advanced calibration procedures in particular in the case of one specific sensor: a differential calorimeter used to quantify nuclear heating. The last one consists in the development of accurate measurement and analysis methods. The paper will be dedicated to a complete review of the experimental and numerical works performed since 2009 thanks to two parts. The first part will detail a new thermal approach implemented to improve nuclear heating measurements by radiometric calorimeters. New experimental tools (calorimeter prototypes and set-ups such BETHY Bench) developed to perform preliminary out-of-pile studies under suitable conditions will be presented (temperature and velocity of the external cooling fluid, heat source localization and intensity inside the calorimetric cells). Then the response of two kinds of sensors, their calibrations curves and their thermal behaviors will be compared for various parameters. Finally validated numerical thermal and Monte Carlo works will be discussed to propose new improvements. The second parts of the paper will focus on works realized in order to design, develop and test the first prototype of the multi-sensor device called CARMEN [7-9]. The two mock-ups dedicated respectively to neutron measurements and photon measurements will be detailed. The results obtained during two irradiation campaigns inside the periphery of OSIRIS reactor will be shown. The new analysis method will be discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Parallel algorithms for finding connected components using linear algebra

Finding connected components is one of the most widely used operations on a graph. Optimal serial algorithms for the problem have been known for half a century, and many competing parallel algorithms have been proposed over the last several decades under various different models of parallel computation. This paper presents a class of parallel connected-component algorithms designed using linear-algebraic primitives. These algorithms are based on a PRAM algorithm by Shiloach and Vishkin and can be designed using standard GraphBLAS operations. Here, we demonstrate two algorithms of this class, one named LACC for Linear Algebraic Connected Components, and the other named FastSV which can be regarded as LACC’s simplification. With the support of the highly-scalable Combinatorial BLAS library, LACC and FastSV outperform the previous state-of-the-art algorithm by a factor of up to 12x for small to medium scale graphs. For large graphs with more than 50B edges, LACC and FastSV scale to 4K nodes (262K cores) of a Cray XC40 supercomputer and outperform previous algorithms by a significant margin. This remarkable performance is accomplished by (1) exploiting sparsity that was not present in the original PRAM algorithm formulation, (2) using high-performance primitives of Combinatorial BLAS, and (3) identifying hot spots and optimizing them away by exploiting algorithmic insights.

97 MATHEMATICS AND COMPUTING↗