Search NASA⌕ Search

SEARCH · Search NASA

Results for “batch 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.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Application of a Monte Carlo accuracy assessment tool to TDRS and GPS

In support of a NASA study on the application of radio interferometry to satellite orbit determination, MITRE developed a simulation tool for assessing interferometric tracking accuracy. Initially, the tool was applied to the problem of determining optimal interferometric station siting for orbit determination of the Tracking and Data Relay Satellite (TDRS). Subsequently, the Orbit Determination Accuracy Estimator (ODAE) was expanded to model the general batch maximum likelihood orbit determination algorithms of the Goddard Trajectory Determination System (GTDS) with measurement types including not only group and phase delay from radio interferometry, but also range, range rate, angular measurements, and satellite-to-satellite measurements. The user of ODAE specifies the statistical properties of error sources, including inherent observable imprecision, atmospheric delays, station location uncertainty, and measurement biases. Upon Monte Carlo simulation of the orbit determination process, ODAE calculates the statistical properties of the error in the satellite state vector and any other parameters for which a solution was obtained in the orbit determination. This paper presents results from ODAE application to two different problems: (1)determination of optimal geometry for interferometirc tracking of TDRS, and (2) expected orbit determination accuracy for Global Positioning System (GPS) tracking of low-earth orbit (LEO) satellites. Conclusions about optimal ground station locations for TDRS orbit determination by radio interferometry are presented, and the feasibility of GPS-based tracking for IRIDIUM, a LEO mobile satellite communications (MOBILSATCOM) system, is demonstrated.

Pavloff, Michael S.↗
NASA NTRS1975

A Standard Kinematic Model for Flight Simulation at NASA Ames

A standard kinematic model for aircraft simulation exists at NASA-Ames on a variety of computer systems, one of which is used to control the flight simulator for advanced aircraft (FSAA). The derivation of the kinematic model is given and various mathematical relationships are presented as a guide. These include descriptions of standardized simulation subsystems such as the atmospheric turbulence model and the generalized six-degrees-of-freedom trim routine, as well as an introduction to the emulative batch-processing system which enables this facility to optimize its real-time environment.

Mcfarland, R. E.↗
NASA NTRS1986

Estimating Transient Pressure Surges in Cryogenic Systems

Potentially-damaging pressure waves anticipated and, therefore, avoided. Mathematical model developed for prediction of pressure behavior in single-and two-phase cryogenic systems. Transient liquid-flow analysis modified to incorporate behavior of vapor bubbles and used to predict maximum pressure in cryogenic transfer systems consisting of complex pipe and valve arrangements under both steady-state and transient conditions. Simulation compared favorably with data obtained during transfer of liquid oxygen from ground storage tanks to Space Shuttle orbiter external tanks. Program written in FORTRAN 77 for batch execution.

Pfister, P.↗
NASA NTRS2010

Performance Testing of Molten Regolith Electrolysis with Transfer of Molten Material for the Production of Oxygen and Metals on the Moon

Previously, we have demonstrated the production of oxygen by electrolysis of molten regolith simulants at temperatures near 1600 C. Using an inert anode and suitable cathode, direct electrolysis (no supporting electrolyte) of the molten silicate is carried out, resulting in the production of molten metallic products at the cathode and oxygen gas at the anode. Initial direct measurements of current efficiency have confirmed that the process offer potential advantages of high oxygen production rates in a smaller footprint facility landed on the moon, with a minimum of consumables brought from Earth. We now report the results of a scale-up effort toward the goal of achieving production rates equivalent to 1 metric ton O2/year, a benchmark established for the support of a lunar base. We previously reported on the electrochemical behavior of the molten electrolyte as dependent on anode material, sweep rate and electrolyte composition in batches of 20-200g and at currents of less than 0.5 A. In this paper, we present the results of experiments performed at currents up to 10 Amperes) and in larger volumes of regolith simulant (500 g - 1 kg) for longer durations of electrolysis. The technical development of critical design components is described, including: inert anodes capable of passing continuous currents of several Amperes, container materials selection, direct gas analysis capability to determine the gas components co-evolving with oxygen. To allow a continuous process, a system has been designed and tested to enable the withdrawal of cathodically-reduced molten metals and spent molten oxide electrolyte. The performance of the withdrawal system is presented and critiqued. The design of the electrolytic cell and the configuration of the furnace were supported by modeling the thermal environment of the system in an effort to realize a balance between external heating and internal joule heating. We will discuss the impact these simulations and experimental findings have on the design of a suitable prototype for lunar applications

Sibille, Laurent↗
DOE OSTI2023

Investigation of the Effect of Chrome and Nickel Concentrations During Two-Piston Splat Quenching of Austenitic Stainless Steels

For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Stellar Photometry Software

We describe the Stellar Photometry Software (SPS), which combines in a single program procedures for locating stars, computing a mean stellar point-spread function (PSF), and performing aperture and/or multiple PSF-fitting photometry, along with related bookkeeping functions. The software can be run either interactively or in batch mode on computers using the UNIX operating system. The performance of SPS is compared to that of the photometry programs DoPHOT and IRAF/DAOPHOT, using both real and simulated CCD observations. A direct comparison of the instrumental magnitudes shows that all three programs produce comparable results.

Janes, Kenneth A.↗
DOE OSTI2022

Removal and recovery of ammonia from simulated wastewater using Ti3C2Tx MXene in flow electrode capacitive deionization

Abstract Flowing electrode capacitive deionization systems (FE-CDI) have recently garnered attention because of their ability to prevent cross contamination and operate in uninterrupted cycles ad infinitum. Typically, FE-CDI electrodes suffer from low conductivity, reducing deionization performance. Utilization of higher mass loadings to combat this leads to poor rheological properties. Herein, Ti 3 C 2 T x MXene was introduced as 1 mg mL −1 slurry electrodes in an FE-CDI system for the removal and recovery of ammonia from simulated agricultural wastewater. The electrode performance was evaluated by operating the FE-CDI system with a feed solution of 500 mg L −1 NH 4 Cl running in batch mode at a constant voltage of 1.20 and −1.20 V in charging and discharging modes, respectively. Despite the low loading, Ti 3 C 2 T x flowing electrodes showed markedly improved performance, achieving 60% ion removal efficiency in a saturation time of 115 min with an adsorption capacity of 460 mg g −1 . To understand the high adsorption performance of the electrodes, physiochemical and structural analysis was done via a variety of characterization techniques such as SEM, TEM, XRD, DLS, and Raman spectroscopy. Cyclic voltammetry and galvanostatic charge/discharge profiles were obtained to evaluate the electrochemical properties of the electrodes. The system proved to be an energy-saving technology by exhibiting a charge efficiency of 58–70% while operating at an energy consumption of 0.45 kWh kg −1 . A 92% regeneration efficiency showed that the electrodes were stable and suitable for long term and scalable usage. The results demonstrate that MXenes have the potential to improve the FE-CDI process for energy-efficient removal and recovery of ammonia.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Algorithms for onboard orbit estimation with Tracking and Data Relay Satellite System data

An investigation is carried out to determine an appropriate estimation technique for onboard orbit determination using simulated Tracking and Data Relay Satellite System (TDRSS) data. Results are presented from studies done using three estimation techniques: an extended Kalman filter, a consider filter, and a sliding batch differential corrector. These estimators are evaluated when used with both baseline and worst-case TDRSS measurement errors and with tracking configurations for two types of orbits: a high-inclination, near-circular orbit with an altitude of 700 km and a moderately inclined, lower altitude orbit. Each estimation result is evaluated by comparing the true with the estimated ephemeris.

Dunham, J. B.↗
DOE OSTI2024

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↗
DOE OSTI2022

Simulation of Bunch Formation for the Mu2e Experiment

The Fermilab Recycler is an 8 GeV storage ring composed of permanent magnets that was crucial to the success of the Fermilab Tevatron Collider program. It is currently being used to slip-stack protons for the high energy neutrino program and to re-bunch protons for use in the Muon g-2 and Mu2e experiments. For the latter applications, the Recycler re-bunches each 1.6 µs "batch" from the Fermilab Booster into four 2.5 MHz bunches. For the Mu2e experiment, it is crucial that beam more than 125 ns from the nominal bunch center be suppressed by at least a factor of 1E-5. While bunch formation is currently in operation for the g-2 experiment, this out of time requirement has not been met, and the reason is not understood. This work presents a simulation of bunch formation in the Recycler, in an effort to understand the reason for this excessive out of time beam and to search for a way to reduce it.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis

Abstract Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

User guide for the Geospatial Risk Analysis Tool (V.1.0.1)

Developed by the Pacific Northwest National Laboratory (PNNL), the Geospatial Risk Analysis Tool (GRAT) links to Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), a complete system for computing simple air parcel trajectories, as well as complex transport, dispersion, chemical transformation, and deposition simulations. The HYSPLIT model was developed by the National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory and the Australian Bureau of Meteorology Research Center in 1998. GRAT is used to batch process meteorological data into ARL format. While HYSPLIT GUI limits users to convert meteorological data up to 6 date time points per operation, GRAT enables users to convert a significantly large amount of data (For example, 10 years of meteorological data measured with an interval of 5 minutes) within one operation. Incorporated with the Potential source distribution function (PSDF), GRAT can also be used to determine the areas influenced by the emission of hazardous chemicals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing

The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D projects on Amazon Web Services and Google Cloud as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures. The proof of concept phases have concluded with the cloud-native, vendoragnostic integration with the experiment’s data and workload management frameworks. Google Cloud has been used to evaluate elastic batch computing, ramping up ephemeral clusters of up to O(100k) cores to process tasks requiring quick turnaround. Amazon Web Services has been exploited for the successful physics validation of the Athena simulation software on ARM processors. We have also set up an interactive facility for physics analysis allowing endusers to spin up private, on-demand clusters for parallel computing with up to 4 000 cores, or run GPU enabled notebooks and jobs for machine learning applications. The success of the proof of concept phases has led to the extension of the Google Cloud project, where ATLAS will study the total cost of ownership of a production cloud site during 15 months with 10k cores on average, fully integrated with distributed grid computing resources and continue the R&D projects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗
DOE OSTI2025

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗