Search NASA⌕ Search

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.

At least 1,333 records · Page 74

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials

We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Summertime low clouds mediate the impact of the large-scale circulation on Arctic sea ice

The rapid Arctic sea ice retreat in the early 21 st century is believed to be driven by several dynamic and thermodynamic feedbacks, such as ice-albedo feedback and water vapor feedback. However, the role of clouds in these feedbacks remains unclear since the causality between clouds and these processes is complex. Here, we use NASA CERES satellite products and NCAR CESM model simulations to suggest that summertime low clouds have played an important role in driving sea ice melt by amplifying the adiabatic warming induced by a stronger anticyclonic circulation aloft. The upper-level high pressure regulates low clouds through stronger downward motion and increasing lower troposphere relative humidity. The increased low clouds favor more sea ice melt via emitting stronger longwave radiation. Then decreased surface albedo triggers a positive ice-albedo feedback, which further enhances sea ice melt. Considering the importance of summertime low clouds, accurate simulation of this process is a prerequisite for climate models to produce reliable future projections of Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗

Bayesian Exploration and Surrogate Emulation of Nonlinear Beam-Response Geometry in the LBNF Beamline

Next-generation long-baseline neutrino experiments aim to achieve multi-MW proton beam power while reducing accelerator-induced systematic uncertainties. At Fermilab, the LBNF beamline is designed for 1.2 MW operation with PIP-II and is upgradeable to 2.4 MW. DUNE will probe the three-flavor neutrino paradigm and search for CP violation, requiring precise neutrino-flux normalization and improved control of accelerator-related uncertainties. Within the LBNF beamline, the System for On-Axis Neutrino Detection (SAND) will constrain flux uncertainties using precision near-detector measurements, while the Muon Monitor System (MuMS) will provide beamline diagnostics sensitive to the proton beam, target, and horn configuration. However, the pion phase space relevant for DUNE depends simultaneously on many correlated parameters, including beam centroid, beam width, horn current and alignment, target position, optics shifts, and radiation-induced changes. Consequently, MuMS observables exhibit nonlinear and coupled responses that are difficult to characterize using traditional one-parameter scans. To address this challenge, we are developing a Bayesian Exploration framework coupled to physics-informed surrogate emulators trained on Geant4 beamline simulations. Gaussian-process emulators provide both fast predictions and uncertainty estimates, enabling adaptive selection of new simulation points in beam-parameter space. As an initial demonstration, we construct surrogate emulators for MuMS response observables using a verified simulation campaign spanning proton-beam steering conditions. The emulators reproduce the simulated dependence of MuMS centroid and gradient observables while providing predictive uncertainties, and serve as the foundation for future multidimensional exploration including beam width, horn current, and additional beamline parameters. This work establishes a framework for uncertainty-aware beam monitoring, adaptive simulation campaigns, and rapid beam-response inference for future DUNE operations.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Using Simulation for Launch Team Training and Evaluation

This document describes some of the histor y and uses of simulation systems and processes for the training and evaluation of Launch Processing, Mission Control, and Mission Management teams. It documents some of the types of simulations that are used at Kennedy Space Center (KSC) today and that could be utilized (and possibly enhanced) for future launch vehicles. This article is intended to provide an initial baseline for further research into simulation for launch team training in the near future.

Peaden, Cary J.↗

Realistic Thermographic Simulation of Impact Damage with Quadrupole Method

Flash thermography has been shown to be an effective method for detection of delaminations in carbon fiber reinforced polymer (CFRP) composite structures. Improved understanding of the limitations of the technique can be obtained by simulating the inspection process. Time domain finite difference and finite element methods are well suited for such simulations but can be computationally intensive. An alternate method is to solve the Laplace transform of the heat equation, then invert the Laplace transform to produce a time domain response. Often this is referred to as the thermal quadrupole method and is well suited for simulating flash thermography. The quadrupole method has been used extensively for simulating one-dimensional heat flow in multilayer systems with contact resistances at the interfaces. It is also applicable for three dimensional configurations, in particular for simulation of changes in thermographic response due to delaminations in composites. This presentation discusses three-dimensional simulations with realistic shapes and contact resistances at the interfaces between layers. The results of these simulations are compared to thermography measurements on composites specimens with impact induced delaminations.

thermography↗

High-level fuel fabrication facility designs from discrete-event simulation

Like other industrial processes, the production of metallic nuclear fuels (MNF) requires that fabrication facilities be able to reliably meet production demands, operate efficiently, and adhere to federal and local safety regulations. In turn, the set of design variables employed by such a facility, such as operations policies, infrastructure and machinery purchased, and the type and number of staff hired, directly impact a facility’s ability to satisfy these goals. Therefore, facility designers must carefully determine which set of design variable values optimally satisfies these constraints. In this paper, we explore how values for these high-level design variables, namely hiring requirements, can be determined in the context of nuclear fuel manufacturing through the coupling of physics-based and discrete-event simulation technologies. Using the Versatile Test Reactor (VTR) program as a case study, we demonstrate how SCALE and MCNP nuclear physics model outputs can be integrated into ExtendSim discrete-event simulation (DES) models of the fuel fabrication process to determine the optimal number of staff hired to ensure fuel production goals are met, operations comply with effective dose limit regulations, and overall project costs are reduced.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigating the effect of oxy-fuel combustion and light coal volatiles interaction: A mass spectrometric study

Given the multi-physical nature of coal combustion, the development and validation of detailed chemical models reproducing coal volatiles combustion under oxy-fuel conditions is a crucial step towards the advancement of predictive full-scale simulations. During the devolatilization process, a large variety of gases is released and undergoes secondary pyrolysis and oxidation reactions. Therefore, the ability to capture their interactions is a prerequisite for each chemical model used in its detailed or reduced form to simulate these processes. In this work, a high-resolution time-of-flight molecular-beam mass spectrometer was employed to enable fast and simultaneous detection of stable and unstable species in counterflow flames of typical light volatiles. Following an approach of increasing complexity, carbon dioxide and methane were progressively added to an argon diluted acetylene base flame. For the three flames investigated here, results showed a significant increase in the concentration of C 2 and C 3 hydrocarbons and oxygenated compounds caused by methane addition to the acetylene flame. By hindering the production of the butadienyl radical, the addition of methane induces the reduction of benzene which triggers the decrease of aromatic species. Conversely, CO 2 addition did not have significant effects on intermediates. To guide and interpret the measurements, numerical simulations with two existing chemical models were performed and the results were found to be consistent with the experimental data for small hydrocarbons. Some discrepancies were found between the two model predictions and between simulations and experiments for C 4 and C 5 species. In addition, numerical simulations were found to overestimate the role of the methyl radical in aromatics formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Sud, Y. C.↗

Success of digital adiabatic simulation with large Trotter step

The simulation of adiabatic evolution has deep connections with adiabatic quantum computation, the quantum approximate optimization algorithm, and adiabatic state preparation. Here we address the error analysis problem in quantum simulation of adiabatic process using Trotter formulas. Here we show that with additional conditions, the circuit depth can be linear in simulation time T. The improvement comes from the observation that the fidelity error here can't be estimated by the norm distance between evolution operators. This phenomenon is termed the robustness of discretization in digital adiabatic simulation. It can be explained in three steps, from analytical and numerical evidence: (1) The fidelity error should be estimated by applying adiabatic theorem on the effective Hamiltonian instead. (2) Because of the specialty of Riemann-Lebesgue lemma, most adiabatic process is naturally robust against discretization. (3) As the Trotter step gets larger, the spectral gap of effective Hamiltonian tends to close, which results in the failure of digital adiabatic simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy~ precipitation processes will be discussed.

Tao, Wei-Kuo↗

Two dimensional PIC simulations of plasma heating by the dissipation of Alfven waves

Two dimensional plasma particle simulations of the evolution of large amplitude circularly polarized Alfven waves propagating parallel to the magnetic field show that the waves decay via both one- and two- dimensional parametric decay instabilities. For parameters studied, one-dimensional processes dominate the simulations, but two-dimensional decay processes, including the recently predicted filamentation instability are also observed. The daughter waves generated by the parametric decay are primarily damped by the ions, leading to ion heating. The parametric decay processes efficiently convert the ordered fluid ion motion in the Alfven wave into ion thermal energy. These processes may be important for the dissipation of Alfven waves in the solar wind, the corona and other space plasma environments. The computations were performed on the Intel Touchstone parallel supercomputer.

Liewer, P. C.↗

Effects of Secondary Task Modality and Processing Code on Automation Trust and Utilization During Simulated Airline Luggage Screening

The purpose of this research was to examine the impact of environmental distractions on human trust and utilization of automation during the process of visual search. Participants performed a computer-simulated airline luggage screening task with the assistance of a 70% reliable automated decision aid (called DETECTOR) both with and without environmental distractions. The distraction was implemented as a secondary task in either a competing modality (visual) or non-competing modality (auditory). The secondary task processing code either competed with the luggage screening task (spatial code) or with the automation's textual directives (verbal code). We measured participants' system trust, perceived reliability of the system (when a target weapon was present and absent), compliance, reliance, and confidence when agreeing and disagreeing with the system under both distracted and undistracted conditions. Results revealed that system trust was lower in the visual-spatial and auditory-verbal conditions than in the visual-verbal and auditory-spatial conditions. Perceived reliability of the system (when the target was present) was significantly higher when the secondary task was visual rather than auditory. Compliance with the aid increased in all conditions except for the auditory-verbal condition, where it decreased. Similar to the pattern for trust, reliance on the automation was lower in the visual-spatial and auditory-verbal conditions than in the visual-verbal and auditory-spatial conditions. Confidence when agreeing with the system decreased with the addition of any kind of distraction; however, confidence when disagreeing increased with the addition of an auditory secondary task but decreased with the addition of a visual task. A model was developed to represent the research findings and demonstrate the relationship between secondary task modality, processing code, and automation use. Results suggest that the nature of environmental distractions influence interaction with automation via significant effects on trust and system utilization. These findings have implications for both automation design and operator training.

Phillips, Rachel↗

A Survey of Multizone Airflow Simulation Software

H-Canyon simulates the building and process ventilation to ensure positive contamination control for any modifications as well as evaluating off-normal conditions. Simulations can also be used to identify air quality of personnel occupied areas. The models can be classified into two groups, single and multi-zone models. As the name states, a single zone model assumes that the building can be described by a single, well-mixed zone. Whereas large buildings have structures that must be described as multizone. Multizone airflow models deal with the difficulty of flows in a building by distinguishing the effects of internal flow restrictions. Several models have been developed that take internal partitions into account. CONTAM (currently used) is a multizone airflow program created by NIST to determine airflows including infiltration, exfiltration, wind pressures acting outside the building, buoyancy effects caused by the indoor and outdoor air temperature difference. COMIS is a multizone air infiltration, ventilation, and contaminant transport model that was developed at Lawrence Berkeley National Laboratory. COMIS deals with applied pressure distribution, airflow components, HVAC systems, schedules, and contaminant transport. EnergyPlus is designed by DOE. It supports flexible component level configuration of HVAC models and simulates sub-hourly time steps to control fast dynamic systems. The program features include providing accurate environmental performance data including energy consumption and carbon emissions, and reporting solar gains on surfaces. Heavent is used to model industrial ventilation systems to control airborne contaminants. It's designed based on the American Conference of Governmental Industrial Hygienists (ACGIH) Ventilation manual. DesignBuilder is the most recognized and advanced user interface to EnergyPlus. It gives access to all of the most frequently required simulation capabilities covering building fabric, thermal mass, glazing, shading renewables, and HVAC analysis. The objective of this study is to identify all relevant software available including commercially licensed, freely licensed, and open source, that can be used to simulate large, complex process facility ventilation systems. All discovered software tools are evaluated for salient features and compared to the software tool currently used to simulate the H-Canyon ventilation system. The design criteria of a ventilation system has two basic requirements: Supplying fresh air for the occupants and changing the air in the room sufficiently; therefore, the smells, fumes, and contaminants will be removed. In this study, first, whether the software simulates airflow (infiltration, natural ventilation, and interzonal) or considers them to be inputs is discussed. Second, if indoor contaminant levels are considered; and finally suggestions on how airflow analysis can be more appropriately accounted for when performing airflow simulation of a building. All of the airflow software reviewed for this study can account for constant infiltration and natural ventilation rates that are not affected by changes in indoor and outdoor conditions. Modelling infiltration in EnergyPlus or DesignBuilder are applicable for small buildings and not appropriate for larger buildings like the H-Canyon. The effect of wind on external pressures, infiltration, and natural and mechanical ventilation, can also be calculated using all of these software. These programs have control options to switch between natural to mechanical ventilation modes or both (hybrid). Interzonal airflow can be applied which means one zone can be specified to receive a fixed amount of air from another zone. The following ventilation modeling software is recommended for further testing: CONTAM, COMIS, Heavent. The next step in evaluating the software will consist of creating test facility simulations using evaluation copies of the software.

42 ENGINEERING↗

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗

Experimentation in planetary geology

Laboratory simulations of geological processes on the terrestrial planets are described, summarizing results published during the period 1983-1986. Included are studies of wind-driven processes on Mars and Venus (using the special wind-tunnel facilities at NASA Ames); simulations of shock-induced loss of volatiles from solids; equation-of-state determinations; impact experiments simulating cratering, spallation, regolith formation, and disruption; fluid-flow simulations of channel formation on Mars; and dust studies. The use of the microgravity environment of the Space Station for planetary-geology experiments is briefly considered.

Cintala, Mark J.↗

Landsat Science: 40 Years of Innovation and Opportunity

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Cook, Bruce D.↗

1D EDIPIC

EDIPIC codes were developed for simulation of kinetic effects in low-temperature plasmas. They can be used for simulation of plasmas in electrostatic approximation and include many atomistic and plasma-surface interaction processes needed for simulations of low temperature plasmas. These codes include a detailed model of secondary electron emission induced by electrons and ions. The Monte-Carlo model of electron-neutral collisions and the Langevin model of Coulomb collisions for electrons are also implemented.

Sydorenko, Dmytro↗