Simulation of the transportation and deposition of dust and sand by Martian atmospheric processes.
Dust and sand transportation and deposition by Martian atmospheric processes, discussing facilities necessary for simulation
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Dust and sand transportation and deposition by Martian atmospheric processes, discussing facilities necessary for simulation
The Energy Exascale Earth System Model (E3SM) Land Model (ELM) has been extended to kilometer-scale (km-ELM) resolutions, enabling high-fidelity simulations of terrestrial processes at 1 km x 1 km grid spacing. In ELM, domain decomposition partitions the computational domain across processors, ensuring efficient parallel execution. Currently, round-robin decomposition is applied, providing a straightforward way to distribute computational workload. As ELM continues evolving at the kilometer-scale (km-scale), particularly with integrating lateral flow modeling, decomposition strategies must also account for the increased workload and data movement. This paper introduces a flexible user-defined domain decomposition framework, allowing users to customize domain partitioning based on application requirements. The impact of different decomposition strategies is evaluated across various applications concerning computation, communication, and I/O. Results demonstrate that while 1D partitioning yields superior I/O performance, k-nearest neighbors (KNN) clustering effectively reduces inter-process communication overhead. This study lays the groundwork for scalable partitioning in large-scale land surface simulations, enhancing next-generation Earth system modeling.
Stilbenes are a class of organic compounds with broad-ranging pharmaceutical and agricultural applications, which are typically isolated and purified through recrystallization. We are motivated by reducing experimental waste and optimizing yield via developing predictive simulations for processing-dependent crystal morphologies. Using resveratrol as a model stilbene system, we have developed an approach for simulating crystallization with molecular resolution using on-lattice kinetic Monte Carlo. In this work, we highlight modifications to the Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) software package, which were essential to this application. Key enhancements include the incorporation of non-orthogonal cell shapes and monomer anisotropy approximations using bound hard spheres. This new SPPARKS application has been applied to resveratrol with attachment energy libraries obtained from density functional theory, resulting in excellent agreement with experimental morphology prediction.
It is suggested that the quasi-biennial change in the observed flux of the solar neutrinos is causally related to some non-linear process at the central core of the Sun, being associated with the charge in the central temperature. This process seems to be responsible for the physical adjustment of the internal structure of the Sun. Numerical simulation on this process is able to reproduce the quasi-biennial change in the flux of these neutrinos.
A method was developed to create high-fidelity lunar dust simulants that better match the unique properties of lunar dust than the existing simulants. The new dust simulant is designed to more closely approximate the size, morphology, composition, and other important properties of lunar dust (including the presence of nanophase iron). A two-step process is required to create this dust simulant. The first step is to prepare a feedstock material that contains a high percentage of agglutinate-like particles with iron globules (including nanophase iron). The raw material selected must have the proper mineralogical composition. In the second processing step, the feedstock material from the first step is jet-milled to reduce the particle size to a range consistent with lunar dust.
As part of the Better Buildings Summit 2025, a workshop was developed to simulate the decision process for implementing a set of energy savings measures on an existing building. As part of the workshop a "game" was created around energy savings strategies, and workshop participants selected renovation cards that provided data around the impacts of that renovation choice. Participants then were able to calculate overall savings and payback from the selected retrofit opportunities. This publication has been produced to package the resources used in the activity in an organized document so that the materials can be distributed and reused more broadly. It provides a comprehensive framework for replicating the workshop, including step-by-step instructions, retrofit "game cards" with data points, and facilitation guidance. By using these materials, readers can conduct their own version of this interactive workshop with stakeholders in their networks, such as building owners, energy managers, or policy makers. The goal is to empower users to simulate the decision-making processes for energy projects, foster collaboration, and drive meaningful discussions around cost-effective retrofit opportunities and goal-oriented outcomes.
Real-time simulation of flexible and articulating systems is difficult because of the computational burden of the time varying calculations. The mobile servicing system of the NASA Space Station Freedom will handle heavy payloads by local arm manipulations and by translating along the spline of the Station, it is crucial to have real-time simulation available. To enable such a simulation to be of high fidelity and to be able to be hosted on a modest computer, special care must be made in formulating the structural dynamics. Frontal solution algorithms save considerable time in performing these calculations. In addition, it is necessary to take advantage of parallel processing be compatible to take full advantage of both. An approach is offered which will result in high fidelity, real-time simulation for flexible, articulating systems such as the space Station remote servicing system.
In nature, many complex multi‐physics coupling problems exhibit significant diffusivity inhomogeneity, where one process occurs several orders of magnitude faster than others temporally. Simulating rapid diffusion alongside slower processes demands intensive computational resources due to the necessity for small time steps. To address these computational challenges, we have developed an efficient numerical solver named Finite Difference informed Random Walker (FDiRW). In this study, we propose a GPU‐accelerated, mixed‐precision configuration for the FDiRW solver to maximize efficiency through GPU multi‐threaded parallel computation and lower precision computation. Numerical evaluation results reveal that the proposed GPU‐accelerated mixed‐precision FDiRW solver can achieve a 117× speedup over the CPU baseline, while an additional 1.75× speedup is achieved by employing lower precision GPU computation. Notably, for large model sizes, the GPU‐accelerated mixed‐precision FDiRW solver demonstrates strong scaling with the number of nodes used in simulation. When simulating radionuclide absorption processes by porous wasteform particles with a medium‐sized model of 192 × 192 × 192, this approach reduces the total computational time to 10 min, enabling the simulation of larger systems with strongly inhomogeneous diffusivity.
Global surface energy closure and its variability depends heavily upon the surface radiative energy budget in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance is observed between energy and water fluxes in terms of energy closure in some atmospheric reanalysis systems, implying that processes are not simulated well. A recent paper by Hsaio et al (2023, pre-published version) found that the transition process has wind shear and longwave cloud radiative feedback signatures. In this presentation, we assess the surface radiative budget in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES Ed4.1, ISSCP FH, etc.) and describing the variability across the deep tropics for the period from 1988 to near present. We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear. We include further analysis contrasting 6 key tropical oceanic regions (Indian Ocean east and west, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean) and the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. We conclude with recommendations for continuing work.
Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.
Computational models of the cardiovascular system are powerful adjuncts to ground-based and in-flight experiments. We will provide NSBRI with a model capable of simulating the short-term effects of gravity on cardiovascular function. The model from this project will: (1) provide a rational framework which quantitatively defines interactions among complex cardiovascular parameters and which supports the critical interpretation of experimental results and testing of hypotheses. (2) permit predictions of the impact of specific countermeasures in the context of various hypothetical cardiovascular abnormalities induced by microgravity. Major progress has been made during the first 18 months of the program: (1) We have developed an operational first-order computer model capable of simulating the cardiovascular response to orthostatic stress. The model consists of a lumped parameter hemodynamic model and a complete reflex control system. The latter includes cardiopulmonary and carotid sinus reflex limbs and interactions between the two. (2) We have modeled the physiologic stress of tilt table experiments and lower body negative pressure procedures (LBNP). We have verified our model's predictions by comparing them with experimental findings from the literature. (3) We have established collaborative efforts with leading investigators interested in experimental studies of orthostatic intolerance, cardiovascular control, and physiologic responses to space flight. (4) We have established a standardized method of transferring data to our laboratory from the ongoing NSBRI bedrest studies. We use this data to estimate input parameters to our model and compare our model predictions to actual data to further verify our model. (5) We are in the process of systematically simulating current hypotheses concerning the mechanism underlying orthostatic intolerance by matching our simulations to stand test data from astronauts pre- and post-flight. (6) We are in the process of developing a JAVA version of the simulator which will be distributed amongst the cardiovascular team members. Future work on this project involves modifications of the model to represent a rodent (rat) model, further evaluation of the bedrest astronaut and animal data, and systematic investigation of specific countermeasures.
ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a CubeSat space telescope that operated in low-Earth orbit, having been deployed from the International Space Station in 2017. The spacecraft has achieved sub-arcsecond pointing stability and millikelvin thermal stability over 20-minute observations. A key enabling feature of the ASTERIA mission is the low level of pointing error that has been demonstrated under ASTERIA’s fine pointing control mode. Prior to launch, the ASTERIA mission performed analysis and simulations to estimate the in-flight pointing performance. This analysis used reaction wheel models provided by JPL’s Small Satellite Dynamics Testbed (SSDT), which had performed Kistler table testing to characterize the jitter caused by the reaction wheels of the Blue Canyon Technologies XACT attitude control unit within ASTERIA. These models were subsequently incorporated into the SSDT simulation. The main source of jitter, the high-frequency attitude disturbance over the camera exposure time, on ASTERIA is the set of rotating reaction wheels that are used for maintaining fine pointing during observations. The reaction wheels impart disturbance forces and torques continuously that cause unwanted motion during imaging. Increased jitter consequently leads to blurring of the image. Therefore, to benefit all SmallSat missions devoted to photometric or spectroscopic astrophysics applications, an on-orbit flight data acquisition and jitter testing campaign was performed in an attempt to help validate the SSDT’s simulation models. This paper describes the process used to validate several simulation models and attempt to characterize the ASTERIA jitter by analyzing the size of the resulting spot size for the target stars as a function of wheel speed, having commanded four wheel speeds for each of three stars of known brightness. After summarizing the on-orbit observation and jitter level measurement process, this paper compares the results obtained from the flight operational environment to the corresponding set of simulation jitter levels. Though the flight data obtained during this experiment was not sufficient to validate the simulation’s jitter model, other models have been validated with flight data, including the magnetic field, orbit propagation, sun position, and long-duration orbit decay models, which may be used by all other projects that use the SSDT’s simulation to increase system capability knowledge.
This paper describes the architecture and implementation of a distributed launch and ascent simulation of NASA's Orion spacecraft and Ares I launch vehicle. This simulation is one segment of the Distributed Space Exploration Simulation (DSES) Project. The DSES project is a research and development collaboration between NASA centers which investigates technologies and processes for distributed simulation of complex space systems in support of NASA's Exploration Initiative. DSES is developing an integrated end-to-end simulation capability to support NASA development and deployment of new exploration spacecraft and missions. This paper describes the first in a collection of simulation capabilities that DSES will support.
Bonding labs at both MSFC and the northern Utah production plant prepare bond test specimens which simulate or witness the production of NASA's Reusable Solid Rocket Motor (RSRM). The current process for preparing the bonding surfaces employs 1,1,1-trichloroethane vapor degreasing, which simulates the current RSRM process. Government regulations (e.g., the 1990 Amendments to the Clean Air Act) have mandated a production phase-out of a number of ozone depleting compounds (ODC) including 1,1,1-trichloroethane. In order to comply with these regulations, the RSRM Program is qualifying a spray-in-air (SIA) precision cleaning process using Brulin 1990, an aqueous blend of surfactants. Accordingly, surface preparation prior to bonding process simulation test specimens must reflect the new production cleaning process. The Bonding Lab Statistical Process Control (SPC) program monitors the progress of the lab and its capabilities, as well as certifies the bonding technicians, by periodically preparing D6AC steel tensile adhesion panels with EA-91 3NA epoxy adhesive using a standardized process. SPC methods are then used to ensure the process is statistically in control, thus producing reliable data for bonding studies, and identify any problems which might develop. Since the specimen cleaning process is being changed, new SPC limits must be established. This report summarizes side-by-side testing of D6AC steel tensile adhesion witness panels and tapered double cantilevered beams (TDCBs) using both the current baseline vapor degreasing process and a lab-scale spray-in-air process. A Proceco 26 inches Typhoon dishwasher cleaned both tensile adhesion witness panels and TDCBs in a process which simulates the new production process. The tests were performed six times during 1995, subsequent statistical analysis of the data established new upper control limits (UCL) and lower control limits (LCL). The data also demonstrated that the new process was equivalent to the vapor degreasing process.
In order to improve the cryogenic propellant management technologies for a liquid hydrogen rocket with high specific impulse, JAXA, the University of Tokyo, and the NASA Glenn Research Center have jointly organized a multi-agency model validation collaboration project. As part of this project, JAXA's boiling simulation was validated with NASA's experimental data on vertical pipeline chill-down. Simulation results were in good agreement with the experimental data obtained using an improved boiling model to reproduce the spray flow. This activity achieved liquid hydrogen turbo-pump simulation at JAXA for grasping the boiling flow phenomenon from engine cut-off to re-ignition. This joint research resulted in an international cooperative relationship for discussing the cryogenic propellant management technologies necessary to develop next-generation liquid rockets.
A description is given of the structure and use of a computer program that simulates the operation of a parallel processor simulation system. The program is part of an investigation to determine algorithms that are suitable for simulating continous systems on a parallel processor configuration. The simulator is designed to accurately simulate the problem-solving phase of a simulation study. Care has been taken to ensure the integrity and correctness of data exchanges and to correctly sequence periods of computation and periods of data exchange. It is pointed out that the functions performed during a problem-setup phase or a reset phase are not simulated. In particular, there is no attempt to simulate the downloading process that loads object code into the local, transfer, and mapping memories of processing elements or the memories of the run control processor and the system control processor. The main program of the simulator carries out some problem-setup functions of the system control processor in that it requests the user to enter values for simulation system parameters and problem parameters. The method by which these values are transferred to the other processors, however, is not simulated.
To assess engine performance during the testing of Space Shuttle Main Engines (SSMEs), the design of an optimal altitude diffuser is studied for future Space Transportation Systems (STS). For other Space Transportation Systems, rocket propellant using kerosene is also studied. Methane and dodecane have similar reaction schemes as kerosene, and are used to simulate kerosene combustion processes at various temperatures. The equations for the methane combustion mechanism at high temperature are given, and engine combustion is simulated on the General Aerodynamic Simulation Program (GASP). The successful design of an altitude diffuser depends on the study of a sub-scaled diffuser model tested through two-dimensional (2-D) flow-techniques. Subroutines given calculate the static temperature and pressure at each Mach number within the diffuser flow. Implementing these subroutines into program code for the properties of 2-D compressible fluid flow determines all fluid characteristics, and will be used in the development of an optimal diffuser design.
The paper describes the Distributed Space Exploration Simulation (DSES) Project, a research and development collaboration between NASA centers which focuses on the investigation and development of technologies, processes and integrated simulations related to the collaborative distributed simulation of complex space systems in support of NASA's Exploration Initiative. This paper describes the three major components of DSES: network infrastructure, software infrastructure and simulation development. In the network work area, DSES is developing a Distributed Simulation Network that will provide agency wide support for distributed simulation between all NASA centers. In the software work area, DSES is developing a collection of software models, tool and procedures that ease the burden of developing distributed simulations and provides a consistent interoperability infrastructure for agency wide participation in integrated simulation. Finally, for simulation development, DSES is developing an integrated end-to-end simulation capability to support NASA development of new exploration spacecraft and missions. This paper will present current status and plans for each of these work areas with specific examples of simulations that support NASA's exploration initiatives.