Just-In-Time Workflow Management for DUNE
The poster describes the justIN workflow management system funded by the UK for DUNE and now used for all DUNE centrally managed data processing and simulation
McNab, Andrew [CERN]↗
SEARCH · Search NASA
Results for “process simulation”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Direct Feed High-Level Waste APPS Model Glass Testing (DFHLW APPS) Matrix
This report summarizes the data collected during the batching and melting of the Direct Feed High-Level Waste APPS Model Glass Matrix (DFHLW APPS) to serve as a quality-assured validation of the Aspen Process Performance Simulation (APPS) formulation method. Of 15 glasses tested, 12 satisfied all target property constraints. Two glasses, APPS-05 and -06, formed nepheline on canister centerline cooling heat-treatment and failed the Product Consistency Test response limits. Glass APPS-07-2 formed unacceptably high concentrations of crystals (primarily Na3Nd(PO4)2) when heat treated at 950 °C. All other glasses were found to be satisfactory. The measured property values were compared to predicted values from a set of current models. In many cases the current models were found to be inadequate for design of DFHLW glasses. These models are being adjusted to correct for mispredictions. Other models, e.g., density, toxicity characteristic leaching procedure, and sulfur solubility, are adequate for formulation of DFHLW glasses.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Zero Order Reactioin Kinetics: Enabling the use of Detailed Chemical Kinetics in Combustion Simulations (Final CRADA Report)
This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Gamma Technologies, LLC (GT or Participante), to incorporate the ability to access LLNL chemical kinetics technologies while using GT-SUITE, GT’s market leading engine simulation software. At the end of the project, LLNL has released Zero-RK version 3.5 with zero- and one-dimensional (0-D and 1-D) solver functionality that interfaces with GT’s GT-SUITE v2023 and later releases. GT has tested its product to assure their customers that the interface can provide reduction in chemistry solution time for detailed chemistry simulations. The process has also positioned GT to easily benefit from future improvements of the Zero-RK suite of tools developed under the DOE Vehicle Technologies Office.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
End-To-End Simulation Framework for Injection Molding Process Optimization
Explore the source record for details and available documents.
Garg, Nikhil↗
A Magnetoencephalographic/Encephalographic (MEG/EEG) Brain-Computer Interface Driver for Interactive iOS Mobile Videogame Applications Utilizing the Hadoop Ecosystem, MongoDB, and Cassandra NoSQL Databases
In Phase I, we collected data on five subjects yielding over 90% positive performance in Magnetoencephalographic (MEG) mid-and post-movement activity. In addition, a driver was developed that substituted the actions of the Brain Computer Interface (BCI) as mouse button presses for real-time use in visual simulations. The process was interfaced to a flight visualization demonstration utilizing left or right brainwave thought movement, the user experiences, the aircraft turning in the chosen direction, or on iOS Mobile Warfighter Videogame application. The BCI’s data analytics of a subject’s MEG brain waves and flight visualization performance videogame analytics were stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse. In Phase II portion of the project involves the Emotiv Encephalographic (EEG) Wireless Brain–Computer interfaces (BCIs) allow for people to establish a novel communication channel between the human brain and a machine, in this case, an iOS Mobile Application(s). The EEG BCI utilizes advanced and novel machine learning algorithms, as well as the Spark Directed Acyclic Graph (DAG), Cassandra NoSQL database environment, and also the competitor NoSQL MongoDB database for housing BCI analytics of subject’s response and users’ intent illustrated for both MEG/EEG brainwave signal acquisition. The wireless EEG signals that were acquired from the OpenVibe and the Emotiv EPOC headset can be connected via Bluetooth to an iPhone utilizing a thin Client architecture. The use of NoSQL databases were chosen because of its schema-less architecture and Map Reduce computational paradigm algorithm for housing a user’s brain signals from each referencing sensor. Thus, in the near future, if multiple users are playing on an online network connection and an MEG/EEG sensor fails, or if the connection is lost from the smartphone and the webserver due to low battery power or failed data transmission, it will not nullify the NoSQL document-oriented (MongoDB) or column-oriented Cassandra databases. Additionally, NoSQL databases have fast querying and indexing methodologies, which are perfect for online game analytics and technology. In Phase II, we collected data on five MEG subjects, yielding over 90% positive performance on iOS Mobile Applications with Objective-C and C++, however on EEG signals utilized on three subjects with the Emotiv wireless headsets and (n < 10) subjects from the OpenVibe EEG database the Variational Bayesian Factor Analysis Algorithm (VBFA) yielded below 60% performance and we are currently pursuing extending the VBFA algorithm to work in the time-frequency domain referred to as VBFA-TF to enhance EEG performance in the near future. The novel usage of NoSQL databases, Cassandra and MongoDB, were the primary main enhancements of the BCI Phase II MEG/EEG brain signal data acquisition, queries, and rapid analytics, with MapReduce and Spark DAG demonstrating future implications for next generation biometric MEG/EEG NoSQL databases.
McClay, Wilbert↗
Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization
Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.
42 ENGINEERING↗
Effects of Dust Coagulation on Streaming Instability
Abstract Streaming instability (SI) in dust has long been thought to be a promising process in triggering planetesimal formation in the protoplanetary disks (PPDs). In this study, we present the first numerical investigation that models the SI in the vertically stratified disk together with the dust coagulation process. Our simulations reveal that, even with the initially small dust sizes, because dust coagulation promotes dust size growth, SI can eventually still be triggered. Specifically, dust coagulation, limited only by dust fragmentation, broadens the parameter boundaries obtained from previous SI studies using single dust species. We describe the various stages of dust dynamics along with their size evolution and explore the impact of different dust fragmentation velocities. Implications of these results for realistic PPDs are also discussed.
79 ASTRONOMY AND ASTROPHYSICS↗
Leveraging the signature of heterotrophic respiration on atmospheric CO 2 for model benchmarking
Spatial and temporal variations in atmospheric carbon dioxide (CO 2 ) reflect large-scale net carbon exchange between the atmosphere and terrestrial ecosystems. Soil heterotrophic respiration (HR) is one of the component fluxes that drive this net exchange, but, given observational limitations, it is difficult to quantify this flux or to evaluate global-scale model simulations thereof. Here, we show that atmospheric CO 2 can provide a useful constraint on large-scale patterns of soil heterotrophic respiration. We analyze three soil model configurations (CASA-CNP, MIMICS, and CORPSE) that simulate HR fluxes within a biogeochemical test bed that provides each model with identical net primary productivity (NPP) and climate forcings. We subsequently quantify the effects of variation in simulated terrestrial carbon fluxes (NPP and HR from the three soil test-bed models) on atmospheric CO 2 distributions using a three-dimensional atmospheric tracer transport model. Our results show that atmospheric CO 2 observations can be used to identify deficiencies in model simulations of the seasonal cycle and interannual variability in HR relative to NPP. In particular, the two models that explicitly simulated microbial processes (MIMICS and CORPSE) were more variable than observations at interannual timescales and showed a stronger-than-observed temperature sensitivity. Our results prompt future research directions to use atmospheric CO 2 , in combination with additional constraints on terrestrial productivity or soil carbon stocks, for evaluating HR fluxes.
54 ENVIRONMENTAL SCIENCES↗
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological processes at various scales. The rSHUD toolkit includes pre- and post-processing tools, facilitating reproducibility and automation in hydrological modeling. The utility of rSHUD is demonstrated through case studies of the Shale Hills Critical Zone Observatory in the USA and the Waerma watershed in China. The rSHUD toolkit's ability to quickly and automatically deploy models while ensuring reproducibility has facilitated the implementation of the Global Hydrological Data Cloud (https://ghdc.ac.cn, last access: 1 September 2023), a platform for automatic data processing and model deployment. This work represents a significant advancement in hydrological modeling, with implications for future scenario projections and spatial analysis.
Shu, Lele (ORCID:0000000269034466)↗
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
Abstract. Supercooled liquid clouds are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We take advantage of the Macquarie Island Cloud and Radiation Experiment (MICRE) to perform an analysis of observed and simulated cloud processes over the Southern Ocean in a region and season dominated by supercooled liquid clouds. Using a single-column version of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), we compare two different cloud microphysical schemes to ground-based observations of cloud, precipitation, and radiation over a 2.5-month period (1 January–17 March 2017). Both schemes are able to reproduce aspects of the cloud and radiation observations during MICRE to within the uncertainty of the data when the thermodynamic profile is prescribed with relaxation. There are differences in water mass and representation of reflectivity between the schemes. A sensitivity study of the cloud microphysics schemes, one a bulk one-moment scheme and the other a two-moment scheme with prediction of mass and number, indicates that several key processes create differences between the schemes. Surface radiative fluxes and total water path are highly sensitive to the formation and fall speed of precipitation. The prediction of hydrometeor number with the two-moment scheme yields a better comparison with observed reflectivity and radiative fluxes, despite predicting higher liquid water contents than observed. With the two-moment scheme, we are also able to test the sensitivity of the results to the input of liquid cloud condensation nuclei (CCN) and ice nuclei (IN). The cloud properties and resulting radiative effects are found to be sensitive to the CCN and IN concentrations. More CCN and IN increase liquid and ice water paths, respectively. Thus, both the dynamic environment and aerosols, integrated through the cloud microphysics, are important for properly representing Southern Ocean cloud radiative effects.
58 GEOSCIENCES↗
Experimental validation of co-cure process of honeycomb sandwich structures simulation: adhesive fillet shape and bond-line porosity
Explore the source record for details and available documents.
Daniel Zebrine↗
Facility Requirements and Criteria
Structural requirements for integrated mission control center - communication, data processing, and simulation and checkout facilities
INTEGRATED MISSION CONTROL CENTER /IMCC/↗
A study of high frequency nonlinear combustion instability in baffled annular liquid propellant rocket motors
Computer program contains mathematical model which provides relationship between engine gas dynamics and combustion processes. Mathematically simulated explosions initiate gas disturbances. Design methods for damping disturbances can be studied to prevent future engine shutdown or destruction.
Abreu, A.↗
A survey of local interstellar hydrogen from OAO-2 observations of Lyman alpha absorption
The Wisconsin far ultraviolet spectrometer aboard OAO-2 observed the wavelength region near 1216 A for 69 stars of spectral type B2 or earlier. From the strength of the observed interstellar L sub alpha absorption, atomic hydrogen column densities were derived over distances averaging 300 pc away from the sun. The OAO data were compared to synthetic ultraviolet spectra, originally derived from earlier higher resolution rocket observations, which were computer processed to simulate the effects of absorption by different amounts of hydrogen followed by the instrumental blending.
Savage, B. D.↗
Artificial microfossils - Experimental studies of permineralization of blue-green algae in silica.
A technique has been developed to artificially fossilize microscopic algae in crystalline silica under conditions of moderately elevated temperature and pressure. The technique is designed to simulate geochemical processes thought to have resulted in the preservation of organic microfossils in Precambrian bedded cherts. In degree of preservation and mineralogic setting, the artificially permineralized microorganisms are comparable to naturally occurring fossil algae.
Oehler, J. H.↗
A survey of local interstellar hydrogen from OAO-2 observations of Lyman alpha absorption.
A far UV spectrometer aboard OAO-2 observed the wavelength region near 1216 A for 69 stars of spectral type B2 or earlier. From the strength of the observed interstellar L-alpha absorption, column densities of atomic hydrogen were derived over distances averaging 300 pc away from the sun. Measurements of the equivalent widths of this absorption were found to be inappropriate for deducing column densities because of the blending of nearby strong stellar lines by the 12 A wide instrumental profile of the OAO. Instead, the OAO data were compared with synthetic UV spectra, originally derived from earlier higher-resolution rocket observations, which were computer processed to simulate the effects of absorption by different amounts of hydrogen followed by the instrumental blending.
Savage, B. D.↗
Shuttle mission simulator requirement report, volume 2, revision A
The training requirements of all mission phases for crews and ground support personnel are presented. The specifications are given for the design and development of the simulator, data processing systems, engine control, software, and systems integration.
Burke, J. F.↗
User microprogrammable processors for high data rate telemetry preprocessing
The use of microprogrammable processors for the preprocessing of high data rate satellite telemetry is investigated. The following topics are discussed along with supporting studies: (1) evaluation of commercial microprogrammable minicomputers for telemetry preprocessing tasks; (2) microinstruction sets for telemetry preprocessing; and (3) the use of multiple minicomputers to achieve high data processing. The simulation of small microprogrammed processors is discussed along with examples of microprogrammed processors.
Pugsley, J. H.↗