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At least 1,369 records · Page 76

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NASA NTRS2006

Derivation of Improved Surface and TOA Broadband Fluxes Using CERES-derived Narrowband-to-Broadband Coefficients

Satellites can provide global coverage of a number of climatically important radiative parameters, including broadband (BB) shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA) and surface. These parameters can be estimated from narrowband (NB) Geostationary Operational Environmental Satellite (GOES) data, but their accuracy is highly dependent on the validity of the narrowband-to-broadband (NB-BB) conversion formulas that are used to convert the NB fluxes to broadband values. The formula coefficients have historically been derived by regressing matched polarorbiting satellite BB fluxes or radiances with their NB counterparts from GOES (e.g., Minnis et al., 1984). More recently, the coefficients have been based on matched Earth Radiation Budget Experiment (ERBE) and GOES-6 data (Minnis and Smith, 1998). The Clouds and the Earth's Radiant Energy Budget (CERES see Wielicki et al. 1998)) project has recently developed much improved Angular Distribution Models (ADM; Loeb et al., 2003) and has higher resolution data compared to ERBE. A limited set of coefficients was also derived from matched GOES-8 and CERES data taken on Topical Rainfall Measuring Mission (TRMM) satellite (Chakrapani et al., 2003; Doelling et al., 2003). The NB-BB coefficients derived from CERES and the GOES suite should yield more accurate BB fluxes than from ERBE, but are limited spatially and seasonally. With CERES data taken from Terra and Aqua, it is now possible to derive more reliable NB-BB coefficients for any given area. Better TOA fluxes should translate to improved surface radiation fluxes derived using various algorithms. As part of an ongoing effort to provide accurate BB flux estimates for the Atmospheric Radiation Measurement (ARM) Program, this paper documents the derivation of new NB-BB coefficients for the ARM Southern Great Plains (SGP) domain and for the Darwin region of the Tropical Western Pacific (DTWP) domain.

Khaiyer, Mandana M.↗

DOE OSTI2023

LA100 Equity Strategies

LA100 Equity Strategies is a collaborative effort between LADWP, NREL, UCLA, and Kearns & West that employs an interdisciplinary approach utilizing distinct - but connected - research efforts informed and guided by the project Steering Committee, which met monthly through the duration of the project. Chapters 1 through 4 address recognition and procedural justice through recognition, process, and community strategies, while Chapters 5 through 12 address distributional justice through program and infrastructure strategies. Chapters 13 through 17 provide policy and program strategies. Each chapter provides data, methods, tools, insights, and strategies to help LADWP make data-driven, community-informed decisions for equitable investments and program development.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

DOE OSTI2022

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. Here, the suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13% on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Phase modulation failsafe system for multi-kJ lasers based on optical heterodyne detection

Amplification of the transverse scattered component of stimulated Brillouin scattering (SBS) can contribute to optical damage in the large aperture optics of multi-kJ lasers. Because increased laser bandwidth from optical phase modulation (PM) can suppress SBS, high energy laser amplifiers are injected with PM light. Phase modulation distributes the single-frequency spectrum of a master oscillator laser among individual PM sidebands, so a sufficiently high modulation index β can maintain the fluence for all spectral components below the SBS threshold. To avoid injection of single frequency light in the event of a PM failure, a high-speed PM failsafe system (PMFS) must be employed. Because PM is easily converted to AM, essentially all PM failsafes detect AM, with the one described here employing a novel configuration where optical heterodyne detection converts PM to AM, followed by passive AM power detection. Although the PMFS is currently configured for continuous monitoring, it can also detect PM for pulse durations ≥2 ns and could be modified to accommodate shorter pulses. This PMFS was deployed on the Z-Beamlet Laser (ZBL) at Sandia National Laboratories, as required by an energy upgrade to support programs at Sandia’s Z Facility such as magnetized liner inertial fusion. Depending on the origin of a PM failure, the PMFS responds in as little as 7 ns. In the event of an instantaneous failure during initiation of a laser shot, this response time translates to a 30–50 ns margin of safety by blocking a pulse from leaving ZBL’s regenerative amplifier, which prevents injection of single frequency light into the main amplification chain. In conclusion, the performance of the PMFS, without the need for operator interaction, conforms to the principles of engineered safety.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

Evaluation of Sandia NCS Benchmark Suite Updates

The Sandia Nuclear Criticality Safety (NCS) program’s benchmark suite was recently updated. This suite is used to ensure that NCS calculations using computer-based neutron transportation codes have an established baseline comparison of calculated versus known experimental results. The Evaluated Nuclear Data File (ENDF) version used for the MCNP models in the suite was changed from ENDF/B-VII.1 to ENDF/B-VIII.0. Additionally, relevant thermal scattering law data libraries (TSLs) were updated. The sensitivity of the calculational bias of each benchmark model to these changes is discussed. Implementation of the ENDF/B-VIII.0 library and updated TSLs results in improvements to bias distribution in the intermediate enriched uranium, plutonium, and mixed uranium–plutonium (IEU, PU, and MIX) fissionable material benchmark categories, but a small bias increase in low- and high-enriched uranium categories (LEU and HEU, respectively). The results also highlight the sensitivity of the benchmarks, with average lethargy of neutrons causing fission energies (EALF) in the intermediate energy range to ENDF/B library changes. The most numerous bias changes were observed in the thermal energy region when transitioning from ENDF/B-VII.1 to ENDF/B-VIII.0. In conclusion, most of the unique bias changes observed in MCNP 6.3.0 between the two nuclear data libraries were in the LEU-COMP-THERM evaluation subset.

ICSBEP↗

DOE OSTI2018

Correlated prompt fission data in transport simulations

Detailed information on the fission process can be inferred from the observation, modeling and theoretical understanding of prompt fission neutron and γ-ray observables. Beyond simple average quantities, the study of distributions and correlations in prompt data, e.g., multiplicity-dependent neutron and γ-ray spectra, angular distributions of the emitted particles, n -n, n - γ, and γ - γ correlations, can place stringent constraints on fission models and parameters that would otherwise be free to be tuned separately to represent individual fission observables. The FREYA and CGMF codes have been developed to follow the sequential emissions of prompt neutrons and γ rays from the initial excited fission fragments produced right after scission. Both codes implement Monte Carlo techniques to sample initial fission fragment configurations in mass, charge and kinetic energy and sample probabilities of neutron and γ emission at each stage of the decay. This approach naturally leads to using simple but powerful statistical techniques to infer distributions and correlations among many observables and model parameters. The comparison of model calculations with experimental data provides a rich arena for testing various nuclear physics models such as those related to the nuclear structure and level densities of neutron-rich nuclei, the γ-ray strength functions of dipole and quadrupole transitions, the mechanism for dividing the excitation energy between the two nascent fragments near scission, and the mechanisms behind the production of angular momentum in the fragments, etc. Beyond the obvious interest from a fundamental physics point of view, such studies are also important for addressing data needs in various nuclear applications. The inclusion of the FREYA and CGMF codes into the MCNP6.2 and MCNPX - PoliMi transport codes, for instance, provides a new and powerful tool to simulate correlated fission events in neutron transport calculations important in nonproliferation, safeguards, nuclear energy, and defense programs. Here, this review provides an overview of the topic, starting from theoretical considerations of the fission process, with a focus on correlated signatures. It then explores the status of experimental correlated fission data and current efforts to address some of the known shortcomings. Numerical simulations employing the FREYA and CGMF codes are compared to experimental data for a wide range of correlated fission quantities. The inclusion of those codes into the MCNP6.2 and MCNPX - PoliMi transport codes is described and discussed in the context of relevant applications. The accuracy of the model predictions and their sensitivity to model assumptions and input parameters are discussed. Lastly, a series of important experimental and theoretical questions that remain unanswered are presented, suggesting a renewed effort to address these shortcomings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Instrumentation for the Investigation of Pitch Bearing Design and Reliability

Recently, there has been an increasing level of industry interest in pitch system and pitch bearing reliability. Pitch bearings are used in wind turbines to connect the blade root to the hub. Some populations of pitch bearings have demonstrated a 12% failure rate in 20 years. As rotor diameters continue to increase for tall land-based and offshore wind turbines, pitch bearings are becoming even larger in diameter, which can make them vulnerable to deflections and consequent stress concentrations. There is an increased need to more accurately study pitch bearing deformations, misalignment, load distributions, and contact stresses. A significant body of work has investigated fatigue lives and wear characteristics of pitch bearings on ground-based test rigs. NREL has also recently begun a research program related to pitch bearing reliability, recognizing its growing importance for wind turbines. The purpose of this paper is to describe a set of instrumentation that was recently installed on a 1.5 MW wind turbine at the NREL Flatirons Campus and provide an example data set. To the authors' knowledge, this will be the first publicly available pitch bearing data collection campaign on an operational wind turbine.

17 WIND ENERGY↗

DOE OSTI2026

E2C Cohort on Major Energy Disruptions in the Southeast: Trade-Offs and Feasibility of Energy Sector Investment for Community Resilience [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the tradeoffs and relative costs of different strategies to improve outcomes from these extreme events. The workshop is on May 21, 2026.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Evaluation of flow-induced plate deflection for University of Missouri research reactor low-enriched uranium fuel element

The University of Missouri Research Reactor (MURR), located on the campus of the University of Missouri in Columbia, Missouri, is one of the six United States (U.S.) High Performance Research Reactors (USHPRR), including one critical facility, that are actively collaborating with the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) Office of Material Management and Minimization (M3) Reactor Conversion Program to convert from highly enriched uranium (HEU, ≥20 wt% U-235) fuel to low-enriched uranium (LEU, <20 wt% U-235) fuel. A new type of very high-density LEU fuel based on a monolithic alloy of uranium and 10 wt% molybdenum (U-10Mo) is expected to allow conversion of some USHPRR, including MURR. In the design of its fuel elements, MURR is using thin parallel curved fuel plates separated by coolant channels. In this work, fluid-structure interaction (FSI) analysis of the MURR LEU fuel element is performed at the element level (as compared to the plate level analysis), which models all components of the LEU fuel element, including fuel plates and the supporting structures. Therefore, the effect of supporting structures on the flow distribution within the element and the fuel plate deflection are evaluated. In addition to the element nominal flow rate and dimensions, the tolerances in the geometry of the coolant channel and plate thickness, the effect of a comb on plate deflection, and the uncertainty of the flow rate per element are evaluated. For the LEU fuel plates, which are thinner than the current HEU plates, the predicted plate deflection is found to be small compared to the fabrication and assembly tolerances. Thus, the FSI-induced deflections are not expected to noticeably reduce the coolant flow rate or predicted safety margins in the limiting channels for the MURR LEU fuel element. In addition to the simulation work, a hydraulic performance test of the MURR LEU fuel element is currently being planned to support conversion to the use of LEU fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1985

In situ orbital debris experiment concepts

Implementation of the radar, lidar and passive optical remote sensing concepts for measuring space debris from an Earth orbiting platform was investigated. Each system was compared for their requirements on the host platform, their performance relative to the space debris measurement program and the estimated cost of developing each concept into a flight instrument. It is found that the radar and lidar systems offer the greatest versatility and accuracy since they control the direction, intensity and duration of the energy incident on the target object. The performance of the passive optical system is determined by the capability of the detector and by the baseline separation of the telescopes, which requires the use of an on-orbit deployment mechanism. The passive optical concept provides the largest total event rae, and includes significant detections of particle sizes greater than 10 cm to allow correlation with ground based observations of the larger particles. The event rate for the radar system is relatively constant with particle while the lidar system is slightly biased toward the smaller sizes. These event rate differences result from a combination of the debris flux size distribution and the variation of sensitive detection area with particle size for the three concepts.

Neste, S. L.↗

NASA NTRS2017

Mind the Gap: Exploring the Underground of the NASA Space Cancer Risk Model

The REID quantifies the lifetime risk of death from radiation-induced cancer in an exposed astronaut. The NASA Space Cancer Risk (NSCR) 2012 mode incorporates elements from physics, biology, epidemiology, and statistics to generate the REID distribution. The current model quantifies the space radiation environment, radiation quality, and dose-rate effects to estimate a NASA-weighted dose. This weighted dose is mapped to the excess risk of radiation-induced cancer mortality from acute exposures to gamma rays and then transferred to an astronaut population. Finally, the REID is determined by integrating this risk over the individual's lifetime. The calculated upper 95% confidence limit of the REID is used to restrict an astronaut's permissible mission duration (PMD) for a proposed mission. As a statistical quantity characterized by broad, subjective uncertainties, REID estimates for space missions result in wide distributions. Currently, the upper 95% confidence level is over 350% larger than the mean REID value, which can severely limit an astronaut's PMD. The model incorporates inputs from multiple scientific disciplines in the risk estimation process. Physics and particle transport models calculate how radiation moves through space, penetrates spacecraft, and makes its way to the human beings onboard. Epidemiological studies of exposures from atomic bombings, medical treatments, and power plants are used to quantify health risks from acute and chronic low linear energy transfer (LET) ionizing radiation. Biological studies in cellular and animal models using radiation at various LETs and energies inform quality metrics for ions present in space radiation. Statistical methodologies unite these elements, controlling for mathematical and scientific uncertainty and variability. Despite current progress, these research platforms contain knowledge gaps contributing to the large uncertainties still present in the model. The NASA Space Radiation Program Element (SRPE) defines the knowledge gaps that impact our understanding of the cancer risks. These gaps are outlined in NASA's Human Research Roadmap [4], which identifies the research questions and actions recommended for reducing the uncertainty in the current NSCR model and for formulation of future models. The greatest contributors to uncertainty in the current model include radiation quality, dose rate effects, and the transfer of exposure-based risk from other populations to an astronaut population. Future formulations of the risk model may benefit from including other potential sources of uncertainty such as space dosimetry, errors in human epidemiology data, and the impact of microgravity and other spaceflight stressors. Here, we discuss the current capabilities of the NSCR-2012 model and several immediate research needs, highlighting areas expected to have an operational impact on the current model schema. The following subway-style route map outlines the NSCR-2012 model (Green Line), emphasizing the research gaps in the Human Research Roadmap for risk of radiation-induced carcinogenesis (Stops on Dashed Lines). The map diagrams how these research gaps feed specific portions of the model.

Chappell, L. J.↗

DOE OSTI2022

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification: Preprint

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs)at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases - distribution system state estimation (DSSE) and fault identification - are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system monitoring↗

DOE OSTI2021

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome”

Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Kerrigan Cain↗

DOE OSTI2016

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Wang, Bin↗

DOE OSTI2021

AENET–LAMMPS and AENET–TINKER : Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials

Machine-learning potentials (MLPs) trained on data from quantum-mechanics based first-principles methods can approach the accuracy of the reference method at a fraction of the computational cost. To facilitate efficient MLP-based molecular dynamics and Monte Carlo simulations, an integration of the MLPs with sampling software is needed. Here, we develop two interfaces that link the atomic energy network (ænet) MLP package with the popular sampling packages TINKER and LAMMPS. The three packages, ænet, TINKER, and LAMMPS, are free and open-source software that enable, in combination, accurate simulations of large and complex systems with low computational cost that scales linearly with the number of atoms. Scaling tests show that the parallel efficiency of the ænet–TINKER interface is nearly optimal but is limited to shared-memory systems. The ænet–LAMMPS interface achieves excellent parallel efficiency on highly parallel distributed memory systems and benefits from the highly optimized neighbor list implemented in LAMMPS. We demonstrate the utility of the two MLP interfaces for two relevant example applications: the investigation of diffusion phenomena in liquid water and the equilibration of nanostructured amorphous battery materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗