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DOE OSTI2024

Adaptive Laboratory Evolution for Enhanced Performance of Cupriavidus Necator on Formic Acid

The threat of global warming, driven by rising carbon emissions, highlights the need to decarbonize our economy. This requires innovative solutions for managing carbon waste and its effective utilization. One promising method for CO2 capture and sequestration is the electrochemical reduction of CO2 to formic acid, a soluble C1 molecule that can be used to store carbon and energy, and as a feedstock for biological conversion. Cupriavidus necator H16, a soil bacterium capable of consuming and growing on formic acid as its sole carbon and energy source, is well positioned to upgrade CO2-derived formic acid into platform chemicals and fuel precursors. To improve the performance of C. necator on formic acid, adaptive laboratory evolution (ALE), a proven tool for improving microbial fitness, has been conducted using continuous pH-stat bioreactors. The system works on the basis that consumption of formic acid raises the pH and triggers the addition of more formic acid to maintain the pH (in this case 6.7), such that formic acid is provided at the same rate as it is consumed. This system has been coupled with level control to achieve continuous fermentation where cells acquiring mutations that improve growth on formic acid become more abundant in the population, from which they can be isolated and characterized. During developmental experiments it was discovered that formic acid accumulated to inhibitory levels. It was determined that the nitrogen source, ammonium hydroxide, must be tailored to the carbon consumption to avoid formic acid accumulation. The ALE ran in three lineages for approximately 3000 hours and more than 500 generations. Evolved isolates obtained from each lineage demonstrated an increase in growth rate in conjunction with improve formate utilization compared to the parental strain when evaluated in pH-stat bioreactors. The isolates with improved performance were then subjected to whole genome sequencing to identify potentially causative mutations. Mutations in several key genes across different lineages have been found and will be evaluated individually and in combination to identify those that improve growth on formic acid. Incorporating these mutations into production strains has the potential to greatly improve formic acid conversion and further industrial decarbonization.

adaptive laboratory evolution↗

DOE OSTI2017

Final Technical Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

QUEST is a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, University of Southern California, Massachusetts Institute of Technology, University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The Duke effort focused on the development of algorithms and utility software for non-intrusive sparse UQ representations, and on participation in the organization of annual workshops and tutorials to disseminate UQ tools to the community, and to gather input in order to adapt approaches to the needs of SciDAC customers. In particular, fundamental developments were made in (a) multiscale stochastic preconditioners, (b) gradient-based approaches to inverse problems, (c) adaptive pseudo-spectral approximations, (d) stochastic limit cycles, and (e) sensitivity analysis tools for noisy systems. In addition, large-scale demonstrations were performed, namely in the context of ocean general circulation models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Queue wait time prediction in high performance computing (HPC) systems

High Performance Computing (HPC) systems are critical enablers for groundbreaking scientific research across various domains. Efficient resource allocation, facilitated by job scheduling, is paramount for maximizing the utilization of HPC systems. However, the variability in wait times for queued jobs poses challenges for users, necessitating accurate job wait time estimation. This paper explores the influence of job characteristics, including job size (the number of nodes requested and walltime), the queue to which the job is submitted and other resource requirements, on job wait times in leadership-class HPC systems. Focusing on the Theta Cray XC40 and Polaris machines at Argonne National Laboratory, the study evaluates the performance of different supervised learning algorithms in predicting job wait times. It also evaluates the impact of data preprocessing, including outlier detection, Principal Component Analysis (PCA), and feature selection, on the performance of wait time prediction models. The findings reveal insights into the relationship between job characteristics and wait times, offering a foundation for optimizing resource allocation and enhancing user experience. The methodologies and tools developed in this study are adaptable to other leadership-class HPC systems, providing a valuable contribution to the broader HPC community aiming to improve job scheduling efficiency and user satisfaction.

Okafor, Nwamaka↗

DOE OSTI2020

Reconfiguring DNA Nanotube Architectures via Selective Regulation of Terminating Structures

Molecular assemblies inside cells often undergo structural reconfiguration in response to stimuli to alter their function. Adaptive reconfiguration of cytoskeletal networks, for example, enables cellular shape change, movement, and cargo transport and plays a key role in driving complex processes such as division and differentiation. The cellular cytoskeleton is a self-assembling polymer network composed of simple filaments, so reconfiguration often occurs through the rearrangement of its component filaments’ connectivities. DNA nanotubes have emerged as promising building blocks for constructing programmable synthetic analogs of cytoskeletal networks. Nucleating seeds can control when and where nanotubes grow and capping structures can bind nanotube ends to stop growth. Such seeding and capping structure, collectively called termini, can organize nanotubes into larger architectures. However, these structures cannot be selectively activated or inactivated in response to specific stimuli to rearrange nanotube architectures, a key property of cytoskeletal networks. Here we demonstrate how selective regulation of the binding affinity of DNA nanotube termini for DNA nanotube monomers or nanotube ends can direct the reconfiguration of nanotube architectures. Using DNA hybridization and strand displacement reactions that specifically activate or inactivate four orthogonal nanotube termini, we demonstrate that nanotube architectures can be reconfigured by selective addition or removal of unique termini. Lastly, we show how terminus activation could be a sensitive detector and amplifier of a DNA sequence signal. These results could enable the development of adaptive and multifunctional materials or diagnostic tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Retroelement-guided protein diversification abounds in vast lineages of Bacteria and Archaea

Major radiations of enigmatic Bacteria and Archaea with large inventories of uncharacterized proteins are a striking feature of the Tree of Life. The processes that led to functional diversity in these lineages, which may contribute to a host-dependent lifestyle, are poorly understood. Here, we show that diversity-generating retroelements (DGRs), which guide site-specific protein hypervariability, are prominent features of genomically reduced organisms from the bacterial candidate phyla radiation (CPR) and as yet uncultivated phyla belonging to the DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota and Nanohaloarchaea) archaeal superphylum. From reconstructed genomes we have defined monophyletic bacterial and archaeal DGR lineages that expand the known DGR range by 120% and reveal a history of horizontal retroelement transfer. Retroelement-guided diversification is further shown to be active in current CPR and DPANN populations, with an assortment of protein targets potentially involved in attachment, defence and regulation. Based on observations of DGR abundance, function and evolutionary history, we find that targeted protein diversification is a pronounced trait of CPR and DPANN phyla compared to other bacterial and archaeal phyla. In conclusion, this diversification mechanism may provide CPR and DPANN organisms with a versatile tool that could be used for adaptation to a dynamic, host-dependent existence.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Implementation of ATLAS Distributed Computing monitoring dashboards using InfluxDB and Grafana

For the last 10 years, the ATLAS Distributed Computing project has based its monitoring infrastructure on a set of custom designed dashboards provided by CERN. This system functioned very well for LHC Runs 1 and 2, but its maintenance has progressively become more difficult and the conditions for Run 3, starting in 2021, will be even more demanding; hence a more standard code base and more automatic operations are needed. A new infrastructure has been provided by CERN, based on InfluxDB as the data store and Grafana as the display environment. ATLAS has adapted and further developed its monitoring tools to use this infrastructure for data and workflow management monitoring and accounting dashboards, expanding the range of previous possibilities with the aim to achieve a single, simpler, environment for all monitoring applications. This document describes these tools and the data flows for monitoring and accounting.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Heralded processes on continuous-variable spaces as quantum maps

Heralding processes, which only work when a measurement on a part of the system give the good result, are particularly interesting for continuous-variables. They permit non-Gaussian transformations that are necessary for several continuous-variable quantum information tasks. However if maps and quantum process tomography are commonly used to describe quantum transformations in discrete-variable space, they are much rarer in the continuous-variable domain. Also, no convenient tool for representing maps in a way more adapted to the particularities of continuous variables have yet been explored. In this paper we try to fill this gap by presenting such a tool.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

PHANOTATE: a novel approach to gene identification in phage genomes

Motivation: Currently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design, they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present PHANOTATE, a novel method for gene calling specifically designed for phage genomes. Although the compact nature of genes in phages is a problem for current gene annotators, we exploit this property by treating a phage genome as a network of paths: where open reading frames are favorable, and overlaps and gaps are less favorable, but still possible. We represent this network of connections as a weighted graph, and use dynamic programing to find the optimal path. Results: We compare PHANOTATE to other gene callers by annotating a set of 2133 complete phage genomes from GenBank, using PHANOTATE and the three most popular gene callers. We found that the four programs agree on 82% of the total predicted genes, with PHANOTATE predicting more genes than the other three. We searched for these extra genes in both GenBank’s non-redundant protein database and all of the metagenomes in the sequence read archive, and found that they are present at levels that suggest that these are functional protein-coding genes. Availability and implementation: https://github.com/deprekate/PHANOTATE. Supplementary information: Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Quantification of organ motion based on an adaptive image-based scale invariant feature method

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

NATURF

The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (NATURF) is a Python workflow that generates les readable by the Weather Research and Forecasting (WRF) model. The NATURF Python modules use shapefiles containing building footprint and height data as input to calculate 132 building parameters at any resolution and converts the parameters into a binary file format.

Allen-Dumas, MelissaRee [Oak Ridge National Lab. (↗

DOE OSTI2025

PVmesh [SWR-24-123]

PVmesh is an open-source Python tool for generating high-fidelity, adaptive finite-element meshes for photovoltaic modules. It supports multilayer panel geometries, frame details, and mounting zones that are often difficult to mesh robustly with generic workflows. Built on Gmsh, PVmesh automates geometry construction, partitioning, domain/boundary tagging, and export for downstream finite-element solvers.

He, Xin [National Laboratory of the Rockies (NLR),↗

DOE OSTI2020

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Nine Canyon Long-Duration Energy Storage: A Feasibility Study

The Nine Canyon Long Duration Energy Storage (LDES) Feasibility Study explores the technical and economic viability of deploying advanced energy storage technologies at Energy Northwest's (EN) Nine Canyon (9C) Wind Project site in Benton County, Washington. Supported by the Washington State Department of Commerce and the U.S. Department of Energy’s Office of Electricity under its LDES Voucher Program, the study represents a collaborative effort between EN, Pacific Northwest National Laboratory (PNNL), and ARES North America. At the core of this effort is the development of a generalized techno-economic modeling framework and evaluation tool designed to assess the value proposition of LDES projects across a variety of contexts. The modeling tool is technology-agnostic and accommodates user-defined parameters such as rated power, energy duration, round-trip efficiency, capital and operational costs, and dispatch constraints. It also integrates economic inputs, including market prices, energy revenue structures, and financing parameters to evaluate performance through key metrics. The tool provides utilities with a transparent, adaptable platform to support decision-making, investment prioritization, and portfolio planning for various storage technologies. To guide scenario design and interpretation, the study first surveyed the LDES technology landscape, including lithium-ion batteries, flow batteries, non-hydro gravity storage, and thermo-mechanical systems, comparing cost trajectories, technical performance, safety and hazards, materials sourcing and recyclability, and spatial/siting considerations. This literature-grounded review highlights technology trade-offs and reinforces the need to align technology choice with site characteristics, use cases, and project objectives. A companion chapter examines ownership structures (EN ownership, third-party ownership, shared models) and offtake options (energy marketing, capacity/energy PPAs, time-of-use PPAs, block-delivery PPAs, and tolling), where PPAs (power purchase agreements) represent contractual arrangements for buying and selling electricity. The chapter also highlights implications for risk allocation, capital access, operational control, and revenue certainty. The study also evaluates supervisory control and data acquisition (SCADA) and transmission interconnection pathways, options include upgrading the existing SCADA or deploying a dedicated LDES controller, with attention to protection schemes, data telemetry, cybersecurity, and regulatory coordination with BPA. In addition, an ARES-specific geotechnical and hydrology assessment presented in the appendix screens multiple corridors for slope stability, bearing capacity, cut-and-fill magnitude, and stormwater behavior.

25 ENERGY STORAGE↗

DOE OSTI2026

Modeling Wind in Agrivoltaics and its Impact on Eddy Covariance Flux Measurements

Silicon Ranch is conducting a research study at their 138MW Bancroft Station agrivoltaics site, the largest agrivoltaics research array in the US, in which they are using an eddy covariance flux tower to measure the carbon budget. They are interested in finding out if the presence of the panels changes the effectiveness of these measurements. To investigate this topic, NLR performed numerical simulations of wind through the agrivoltaic array to identify under what environmental conditions (wind speed, wind direction, temperatures) and panel tilt angles the mean wind speeds at the measurement heights are significantly altered by the presence of the solar panels. NLR adapted and used the PVade simulation tool [1] to model wind in Silicon Ranch's agrivoltaic array and found that at the height of the flux tower (6m), the wind speed measured is not significantly altered by the presence of solar panels. The percent difference is less than 4% and is generally greatest during daytime conditions at higher wind speeds and perpendicular wind direction. Closer to the ground, the flow is significantly altered (wind speeds are reduced) by the presence of solar panels and the percent difference increases in strong winds. The work confirmed that eddy covariance flux towers can be used within the context of a solar array field.

14 SOLAR ENERGY↗

NASA NTRS1976

Applications of remote sensing data in Alaska: A cooperative program of the University of Alaska with user organizations, including local, state and federal government agencies

The development of the coastal-zone-related issues is generating an increasing need for information which is greater in quantity of natural resource data, greater in quality of detail of data, and more frequent in collection of data owing to the need to monitor certain aspects of programs. The array, detail, and frequency of information acquisition required to develop natural resources and to implement and maintain the resulting programs demand improved techniques of data gathering, processing, and interpretation which is conducive to the use of remote-sensing techniques. As Alaska, both in the state and federal domain, gears up to meet the energy-related issues facing the nation there will be a growing role for efforts which adapt state-of-the-art tools to solving existing problems.

Miller, J. M.↗

NASA NTRS1986

Factors influencing design and selection of GTAW robotic welding machines for the Space Shuttle main engine

Proposed hardware and software for microprocessor-controlled power supplies and welding machines are described. The application of the automatic seven-axis welding machine, which is to be preprogrammed to allow minimum intervention by the welding operator during the actual process, to the welding of the Space Shuttle main engine is discussed. The production requirements for the gas tungsten arc welds for the Space Shuttle main engine are examined. Consideration is given to positioner design, welding variables, inert shielding gas management, filler metal wire control, the up loading and down loading of data from off-line computers, process improvements, tooling, the welding variable library, and adaptive sensor control.

Flanigan, L.↗

NASA NTRS1987

NASA Office of Space Flight (OSF) in-orbit servicing program

Tools, fixtures and systems being developed to improve the efficiency of extravehicular activity (EVA) servicing operations; and tools developed for EVA use being adapted for use in robot-assisted EVA, local robotic servicing, and remote robotic servicing, are presented. The basic types of satellite servicing operations, the various modes by which they can be accomplished, and the hardware which supports these modes are outlined. The program and hardware elements of the program infrastructure are reviewed.

Levin, George C.↗

NASA NTRS1997

Dynamics of Numerics & Spurious Behaviors in CFD Computations

The global nonlinear behavior of finite discretizations for constant time steps and fixed or adaptive grid spacings is studied using tools from dynamical systems theory. Detailed analysis of commonly used temporal and spatial discretizations for simple model problems is presented. The role of dynamics in the understanding of long time behavior of numerical integration and the nonlinear stability, convergence, and reliability of using time-marching approaches for obtaining steady-state numerical solutions in computational fluid dynamics (CFD) is explored. The study is complemented with examples of spurious behavior observed in steady and unsteady CFD computations. The CFD examples were chosen to illustrate non-apparent spurious behavior that was difficult to detect without extensive grid and temporal refinement studies and some knowledge from dynamical systems theory. Studies revealed the various possible dangers of misinterpreting numerical simulation of realistic complex flows that are constrained by available computing power. In large scale computations where the physics of the problem under study is not well understood and numerical simulations are the only viable means of solution, extreme care must be taken in both computation and interpretation of the numerical data. The goal of this paper is to explore the important role that dynamical systems theory can play in the understanding of the global nonlinear behavior of numerical algorithms and to aid the identification of the sources of numerical uncertainties in CFD.

Yee, Helen C.↗