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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Single-Step Shear-Based Deformation Processing of Electrical Conductor Wires

Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fuel Stratification Effects on Gasoline Compression Ignition with a Regular-Grade Gasoline on a Single-Cylinder Medium-Duty Diesel Engine at Low Load

Prior research studies have investigated a wide variety of gasoline compression ignition (GCI) injection strategies and the resulting fuel stratification levels to maintain control over the combustion phasing, duration, and heat release rate. Previous GCI research at the US Department of Energy’s Oak Ridge National Laboratory has shown that for a combustion mode with a low degree of fuel stratification, called “partial fuel stratification” (PFS), gasoline range fuels with anti-knock index values in the range of regular-grade gasoline (~87 anti-knock index or higher) provides very little controllability over the timing of combustion without significant boost pressures. On the contrary, heavy fuel stratification (HFS) provides control over combustion phasing but has challenges achieving low temperature combustion operation, which has the benefits of low NOX and soot emissions, because of the air handling burdens associated with the required high exhaust gas recirculation rates. Furthermore, this work investigates HFS and PFS combustion, efficiency, and emissions performance on a single-cylinder, medium-duty engine with a regular-grade gasoline (91 research octane number) at 1,200 rpm, 4.3 bar, and 3.0 nominal gross indicated mean effective pressure operating points with boost levels similar to those in a medium-duty diesel application. Authority of combustion phasing with main injection timing sweeps for HFS and second injection timing sweeps and fuel split sweeps for PFS are shown. In addition, this work is discussed in the context of previous findings with a light-duty diesel platform, and next steps and future direction for this work are presented.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Understanding the stability of a plastic‐degrading Rieske iron oxidoreductase system

Abstract Rieske oxygenases (ROs) are a diverse metalloenzyme class with growing potential in bioconversion and synthetic applications. We postulated that ROs are nonetheless underutilized because they are unstable. Terephthalate dioxygenase (TPA DO PDB ID 7Q05 ) is a structurally characterized heterohexameric α 3 β 3 RO that, with its cognate reductase (TPA RED ), catalyzes the first intracellular step of bacterial polyethylene terephthalate plastic bioconversion. Here, we showed that the heterologously expressed TPA DO /TPA RED system exhibits only ~300 total turnovers at its optimal pH and temperature. We investigated the thermal stability of the system and the unfolding pathway of TPA DO through a combination of biochemical and biophysical approaches. The system's activity is thermally limited by a melting temperature ( T m ) of 39.9°C for the monomeric TPA RED , while the independent T m of TPA DO is 50.8°C. Differential scanning calorimetry revealed a two‐step thermal decomposition pathway for TPA DO with T m values of 47.6 and 58.0°C (Δ H = 210 and 509 kcal mol −1 , respectively) for each step. Temperature‐dependent small‐angle x‐ray scattering and dynamic light scattering both detected heat‐induced dissociation of TPA DO subunits at 53.8°C, followed by higher‐temperature loss of tertiary structure that coincided with protein aggregation. The computed enthalpies of dissociation for the monomer interfaces were most congruent with a decomposition pathway initiated by β‐β interface dissociation, a pattern predicted to be widespread in ROs. As a strategy for enhancing TPA DO stability, we propose prioritizing the re‐engineering of the β subunit interfaces, with subsequent targeted improvements of the subunits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Trends in Field and Laboratory Performance of Photovoltaic Modules and Materials

This DuraMAT project intends to identify bill of materials (BOM) and/or process control measures for photovoltaic modules with representative failure modes as informed by accelerated and field tests to guide next steps in module and material design. We have begun work to identify correlation between module field performance and accelerated testing results by cross-comparing a module database of accelerated test results with a module database of fielded systems. We have identified fielded systems with degraded performance, and intend to compare this to the results observed in certification and qualification testing. We also intend to apply lessons and observations from accelerated tests to the field, where it may be possible to mitigate or avoid degradation in the field.

DuraMAT↗
DOE OSTI2023

Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization

The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Challenges in Firmware Re-Hosting, Emulation, and Analysis

System emulation and firmware re-hosting have become popular techniques to answer various security and performance related questions, such as determining whether a firmware contain security vulnerabilities or meet timing requirements when run on a specific hardware platform. While this motivation for emulation and binary analysis has previously been explored and reported, starting to either work or research in the field is difficult. To this end, we provide a comprehensive guide for the practitioner or system emulation researcher. Here, we layout common challenges faced during firmware re-hosting, explaining successive steps and surveying common tools used to overcome these challenges. We provide classification techniques on five different axes, including emulator methods, system type, fidelity, emulator purpose, and control. These classifications and comparison criteria enable the practitioner to determine the appropriate tool for emulation. We use our classifications to categorize popular works in the field and present 28 common challenges faced when creating, emulating, and analyzing a system from obtaining firmwares to post emulation analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A phase-field model for hydraulic fracture nucleation and propagation in porous media

Many geo-engineering applications, for example, enhanced geothermal systems, rely on hydraulic fracturing to enhance the permeability of natural formations and allow for sufficient fluid circulation. Over the past few decades, the phase-field method has grown in popularity as a valid approach to modeling hydraulic fracturing because of the ease of handling complex fracture propagation geometries. However, existing phase-field methods cannot appropriately capture nucleation of hydraulic fractures because their formulations are solely energy-based and do not explicitly take into account the strength of the material. Thus, in this work, we propose a novel phase-field formulation for hydraulic fracturing with the main goal of modeling fracture nucleation in porous media, for example, rocks. Built on the variational formulation of previous phase-field methods, the proposed model incorporates the material strength envelope for hydraulic fracture nucleation through two important steps: (i) an external driving force term, included in the damage evolution equation, that accounts for the material strength; (ii) a properly designed damage function that defines the fluid pressure contribution on the crack driving force. In conclusion, the comparison of numerical results for two-dimensional test cases with existing analytical solutions demonstrates that the proposed phase-field model can accurately model both nucleation and propagation of hydraulic fractures. Additionally, we present the simulation of hydraulic fracturing in a three-dimensional domain with various stress conditions to demonstrate the applicability of the method to realistic scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Demonstration and analysis of volumetric additive manufacturing via sub-orbital spaceflight testing

Computed Axial Lithography (CAL) represents a significant advancement in the emerging field of Volumetric Additive Manufacturing (VAM). CAL addresses key limitations of traditional photopolymer additive manufacturing technologies, by eliminating the need for layering and support structures. Unlike conventional methods, CAL prints components by illuminating all points within a desired geometry simultaneously, using tomographic reconstruction to form the object in a single step. This unique approach eliminates the relative motion between the object and the precursor material, enabling faster printing speeds and reducing the waste associated with support structures. However, CAL parts require post-processing steps before they can be utilized. CAL's core attributes make it particularly suited for In-Space Manufacturing (ISM), due to its fast fabrication times, wide breadth of materials it can use, and minimized footprint. CAL has been successfully demonstrated in microgravity during parabolic flight experiments. However to fully validate and understand CAL's behaviour in microgravity, all manufacturing and post-processing steps must be integrated. In June 2024, we conducted SpaceCAL Mission 3, testing this entire workflow on a suborbital flight aboard Virgin Galactic's SpaceShipTwo. During ~140 s of microgravity, the system autonomously manufactured and post-processed four parts using PEGDA700 resin. Post-flight analysis showed that 2/4 parts were recognisable, while others were distorted due to bubble formation from residual water droplets, off-axis optical aberrations, and non-uniform solvent rinsing. Despite these limitations, this study represents the first integrated CAL workflow in space, providing an initial experimental demonstration and analysis for closed-loop in-space manufacturing.

Waddell, Taylor [Department of Mechanical Engineer↗
DOE OSTI2021

Formation and surface melting of nanoparticle superlattices in a solution

The wisdom in the saying of “There are no two snowflakes alike” lies in the importance of history or kinetic pathways in the phase transitions of solids. Likewise, “artificial solids,” namely superlattices consisting of functional nanoparticles, have lattice size, surface morphology, crystallinity, symmetry, and structural reconfiguration (for example, transition into a disordered state) highly dependent on the kinetic pathways as the nanoparticles interact with each other in solution [1]. Great progresses have been made in understanding the formation pathways of superlattices using liquid-phase transmission electron microscopy (TEM) [2-4]. For example, by tracking single nanoparticle’s trajectories, especially aided by U-net neural network-based machine learning, previous studies mapped the fundamental nanoparticle interactions at nanometer resolution [5]. Nonclassical, two-step nucleation pathway has also been elucidated in the system of nanoprisms, by optimizing protocols such as loading nanoparticle suspensions over the supersaturation threshold and minimizing particle‒substrate interaction [2]. Surface morphologies or exposed facets of superlattices have been shown to follow the principles of Wulff construction rule, where the facet-dependent surface energy can be measured based on the capillary wave theory [4]. However, the reverse process of crystallization of superlattices, the conversion from crystalline to disordered state, has been much less explored. On one hand, the melting of nanoparticle superlattices can provide a preferred pathway to induce structural reorganization or shuffling of building blocks for them to transform into different types of crystal structures. On the other hand, understanding nanoscale superlattice melting and comparing such behaviors with the prevailing surface melting theories developed for atomic/molecular solids can provide a potent way to engineer phase transitions of supra- and hierarchical structures constructed from nanoscale entities (e.g., DNA-coated nanoparticles, proteins), for their applications in reprogrammable and switchable materials with multifunctional properties [6, 7]. The experimental challenges to observe melting of superlattices are twofold. Practically it is difficult to load the initial superlattice form, in an intact manner, into the highly confined liquid-phase TEM chamber for in-situ observation. Here, the triggering of melting also needs meticulous manipulation of nanoparticle concentration, interparticle interaction, and solution environment.

Kim, Ahyoung↗
DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
DOE OSTI2024

Sand Thermal Energy Storage Pilot Design (Final Report)

This report summarizes work done on developing a 10-MWhe pilot of the sand-based thermal energy storage (SandTES) technology at Alabama Power’s Plant Gaston Unit 5, an operating, supercritical coal power unit. The system will be integrated to the unit, obtaining steam to heat the sand through an air-blown fluidized-bed heat exchanger, then storing the water to be reused during discharging to produce steam that will then be vented. An electrical particle heater will also be included to provide part of the heat to the sand to provide data and learnings for commercial systems that will be fully electrically heated. Hot sand is contained in one bunker, while cold sand is housed in the other bunker, and standard solids handling equipment moves the sand around. This pilot would advance the SandTES technology to Technology Readiness Level 6 and position it for commercial readiness by 2030. This work was done in two phases: Phase I performed a conceptual study that provided Association for the Advancement of Cost Engineering (AACE) Class 5 costs and estimated performance, and then Phase II, which also involved a design update, performed a more detailed pre-front-end engineering and design study that elicited AACE Class 4 costs. Work was also done to provide estimated costs for commercial applications of the technology, assess its gaps, create its technology maturation and commercialization plans, and finally perform an Environmental Information Volume for the pilot site as a first step in the National Environmental Policy Act process.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Laboratory and pilot-scale studies of membrane distillation for desalination of produced water from Permian Basin

Substantial quantities of produced water generated during the extraction of oil and gas from unconventional reservoirs present significant environmental concern and increase the operating cost for this industry. Membrane Distillation (MD) can serve as a potential solution for beneficial reuse of produced water by generating high-quality permeate and reducing the volume of produced water requiring disposal. This study investigated treatment of produced water from Permian Basin in both laboratory and pilot-scale studies. Laboratory tests revealed the potential to successfully recover 50% of produced water although some increase in permeate conductivity was observed due to the passage of ammonia from the feed side. Initial pilot-scale test with filtration of raw produced water as the only pre-treatment step led to precipitation of SrSO 4 , NaCl, and Fe in the system once the solubility limits for these salts were exceeded. However, chemical pretreatment that included pH adjustment, aeration, and barite precipitation, allowed successful steady-state operation of the AGMD pilot system for 5 days where the produced water was concentrated from 127 g/L to 255 g/L (~50% water recovery) while recovering high quality permeate. Overall, greater than 99.7 % salt rejection was achieved with the average permeate flux of 1.86 LMH. Finally, mass balance analysis suggested potential Ba and Ca precipitation in the system but there was no impact on AGMD performance and permeate quality during 5 days of continuous operation in the field.

42 ENGINEERING↗
DOE OSTI2020

Kirigami Engineering—Nanoscale Structures Exhibiting a Range of Controllable 3D Configurations

Abstract Kirigami structures provide a promising approach to transform flat films into 3D complex structures that are difficult to achieve by conventional fabrication approaches. By designing the cutting geometry, it is shown that distinct buckling‐induced out‐of‐plane configurations can be obtained, separated by a sharp transition characterized by a critical geometric dimension of the structures. In situ electron microscopy experiments reveal the effect of the ratio between the in‐plane cut size and film thickness on out‐of‐plane configurations. Moreover, geometrically nonlinear finite element analyses (FEA) accurately predict the out‐of‐plane modes measured experimentally, their transition as a function of cut geometry, and provide the stress–strain response of the kirigami structures. The combined computational–experimental approach and results reported here represent a step forward in the characterization of thin films experiencing buckling‐induced out‐of‐plane shape transformations and provide a path to control 3D configurations of micro‐ and nanoscale buckling‐induced kirigami structures. The out‐of‐plane configurations promise great utility in the creation of micro‐ and nanoscale systems that can harness such structural behavior, such as optical scanning micromirrors, novel actuators, and nanorobotics. This work is of particular significance as the kirigami dimensions approach the sub‐micrometer scale which is challenging to achieve with conventional micro‐electromechanical system technologies.

Zhang, Xu↗
DOE OSTI2022

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase I Conceptual Study)

The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and the proposed system is an improvement over alternate low carbon dispatchable power options. Our demonstration will include 54 MWh of hydrogen storage. CO 2 capture inherent to the CHG process can capture 90% of the CO 2 (with upgrades to >98%) in a commercial system (~300 MWth) for sequestration or other uses. The hydrogen will be utilized in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with the existing Southern Company fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load. However, H 2 production is relatively constant by storing H 2 , and revenues are improved by arbitrage between use of low-cost off-peak variable electricity generation or use of stored H 2 under peak demand. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via system requirements review with the whole team. These requirements were then incorporated into/iterated with our Heat & Mass Balance models and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Our system generates power at 17.4% lower cost than other low carbon approaches for the H 2 generation, H 2 compression and storage, carbon sequestration, and HRSG added electricity production for a large-scale duct-fired system. Our team recommends completing the Phase II Pre-FEED study for the proposed system as the next step for the project and its tasks will achieve the overall objective and be ready to launch the FEED. The Pre-FEED tasks include updating the requirements, Concept of Operations, plant scope/process description, component modeling, system modeling, performance estimates, emission estimates, block flow diagrams, fluid/process conditions (PFD), utility usage, and facility sizing/definition. The approach will be to complete these updates in a greater level of detail for the selected site. The approach for developing the EIV is to use the updated results, including model outputs, for carbon dioxide and waste streams.

03 NATURAL GAS↗
DOE OSTI2021

Performance evaluation of a Terry GS-2 steam impulse turbine with air-water mixtures

Terry steam turbines are widely used in various industries because of their robust design. Within the nuclear power generation industry, they are used in the Reactor Core Isolation Cooling System to remove decay heat during reactor isolation events. During the Fukushima Daiichi nuclear power station disaster in Japan in 2011, the Reactor Core Isolation Cooling System and associated Terry turbine operated for over 70 hours in Unit 2; this runtime is well beyond the expected operating duration. Theories suggest the turbine was subjected to a two-phase inlet flow, which could degrade the turbine performance. In this work, an experimental test rig was constructed to test a full-scale Terry model GS-2 steam turbine under two-phase air/water flows. Steady-state efficiency and torque performance maps of the turbine were developed over a range of turbine inlet pressures (1.38–4.83 bar or 20–70 psia), air mass fractions (0.05–1.0) and rotational speeds up to 4000 RPM. Furthermore, turbine performance followed expected trends with torque varying linearly and efficiency varying quadratically with rotational speed. In addition, high-speed images of the two-phase flow entering the turbine were also analyzed to understand how changes in inlet pressure and air mass fraction affect the flow regime and homogenization. The present tests with air–water two-phase mixtures are an important step towards providing an understanding of the full-scale Terry turbine’s behavior and performance curves under two-phase conditions. The results of this work will be combined with air/water and steam/water data gathered using a small-scale Terry ZS-1 steam turbine in order to understand the scaling relationship between large and small size Terry turbines and fluid pairs. The combined data set will enable further development of analytical models over a wide range of conditions and may be used to provide technical justification for expanded use of the Terry turbines in nuclear power plant safety systems and other systems.

42 ENGINEERING↗
DOE OSTI2021

Dynamic structure of active sites in ceria-supported Pt catalysts for the water gas shift reaction

Oxide-supported noble metal catalysts have been extensively studied for decades for the water gas shift (WGS) reaction, a catalytic transformation central to a host of large volume processes that variously utilize or produce hydrogen. There remains considerable uncertainty as to how the specific features of the active metal-support interfacial bonding—perhaps most importantly the temporal dynamic changes occurring therein—serve to enable high activity and selectivity. Here we report the dynamic characteristics of a Pt/CeO 2 system at the atomic level for the WGS reaction and specifically reveal the synergistic effects of metal-support bonding at the perimeter region. We find that the perimeter Pt 0 -O vacancy -Ce 3+ sites are formed in the active structure, transformed at working temperatures and their appearance regulates the adsorbate behaviors. We find that the dynamic nature of this site is a key mechanistic step for the WGS reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Docker Containers for MCNP ® Development

Containers are a revolutionary technology in software development and deployment that provides a lightweight, portable environment for ensuring consistency across multiple computing environments. In anticipation of the MCNP 6.3.1 release, two Docker container images have been released on DockerHub for general use. The MCNP source code is not included in the images, and users are still required to obtain it through RSICC. The images produced by Docker are compliant with the OCI (Open Container Initiative) standards, ensuring compatibility with other container engines such as Podman or Kubernetes’ CRI-O. Initially, the images are stored under the author’s personal space on DockerHub (docker.io/azukaitis), but they will be relocated to a dedicated MCNP group space once approved. In the future, they will also be available through the registry feature of the https://github.com/lanl/mcnp-containers project. The use of Docker provides a pre-configured environment for building and running MCNP, ensuring reproducibility of results across various host architectures. This significantly improves consistency when running MCNP on different systems. Notably, executables and installers from the Docker images have successfully passed the MCNP development branch testing suite on x86-64 architectures, including Windows, macOS, and Linux operating systems. Furthermore, testing has demonstrated compatibility with macOS Docker in emulation mode on the latest Apple Mac M2 Ultra hardware, ensuring robust support even on the latest platforms. In this document, we will provide a step-by-step guide to using the Docker images across multiple platforms. Additionally, we will present performance numbers for building and running the MCNP test suite.

97 MATHEMATICS AND COMPUTING↗