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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.

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At least 55 records · Page 3

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING

Qualitative simulation for process modeling and control

A qualitative model is developed for a first-order system with a proportional-integral controller without precise knowledge of the process or controller parameters. Simulation of the qualitative model yields all of the solutions to the system equations. In developing the qualitative model, a necessary condition for the occurrence of oscillatory behavior is identified. Initializations that cannot exhibit oscillatory behavior produce a finite set of behaviors. When the phase-space behavior of the oscillatory behavior is properly constrained, these initializations produce an infinite but comprehensible set of asymptotically stable behaviors. While the predictions include all possible behaviors of the real system, a class of spurious behaviors has been identified. When limited numerical information is included in the model, the number of predictions is significantly reduced.

Dalle Molle, D. T.

Computational simulation of concurrent engineering for aerospace propulsion systems

Results are summarized of an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulations methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties - fundamental in developing such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering for propulsion systems and systems in general. Benefits and facets needing early attention in the development are outlined.

Chamis, C. C.

Computational simulation for concurrent engineering of aerospace propulsion systems

Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.

Chamis, C. C.

Macro Level Simulation Model Of Space Shuttle Processing

The contents include: 1) Space Shuttle Processing Simulation Model; 2) Knowledge Acquisition; 3) Simulation Input Analysis; 4) Model Applications in Current Shuttle Environment; and 5) Model Applications for Future Reusable Launch Vehicles (RLV's). This paper is presented in viewgraph form.

Source record

Millimeter-Wave Wireless Power Transfer Technology for Space Applications

In this paper we present a new compact, scalable, and low cost technology for efficient receiving of power using RF waves at 94 GHz. This technology employs a highly innovative array of slot antennas that is integrated on substrate composed of gold (Au), silicon (Si), and silicon dioxide (SiO2) layers. The length of the slots and spacing between them are optimized for a highly efficient beam through a 3-D electromagnetic simulation process. Antenna simulation results shows a good beam profile with very low side lobe levels and better than 93% antenna efficiency.

Slot Antenna

Simulation of Landing and Take-Off Noise for Supersonic Transport Aircraft at a Conceptual Design Fidelity Level

The German Aerospace Center has launched an internal project to assess the noise impact associated with supersonic transport aircraft during approach and departure. A dedicated simulation process is established to cover all relevant disciplines, i.e., aircraft and engine design, engine installation effects, flight simulation, and system noise prediction. The core of the simulation process is comprised of methods at the complexity and fidelity level of conceptual aircraft design, i.e., typical overall aircraft design methods and a semi-empirical approach for the noise modeling. Dedicated interfaces allow to process data from high fidelity simulation that will support or even replace initial low fidelity results in the long run. All of the results shown and discussed in this study are limited to the fidelity level of conceptual design. The application of the simulation process to the NASA 55t Supersonic Technology Concept Aeroplane, i.e., based on non-proprietary data for this vehicle, yields similar noise level predictions when compared to the published NASA results. This is used as an initial feasibility check of the new process and confirms the underlying methods and models. Such an initial verification of the process is understood as an essential step due to the lack of available noise data for supersonic transport aircraft in general. The advantageous effect of engine noise shielding on the resulting system noise is demonstrated based on predicted level time histories and certification noise levels. After this initial verification, the process is applied to evaluate a conceptual supersonic transport design based on a PhD thesis with two engines mounted under the wing, which is referred to as aircraft TWO. Full access to this vehicle’s design and performance data allows to investigate the influence of flight procedures on the resulting noise impact along approach and departure. These noise results are then assembled according to proposed Federal Aviation Agency regulations in their Notice of Proposed Rulemaking, e.g., speed limitations, for Supersonic transport noise certification and the regulations from Noise Chapters of the Annex 16 from the International Civil Aviation Organization in order to evaluate the resulting levels as a function of the flight procedure.

noise

Analytical modeling and sensor monitoring for optimal processing of polymeric composite material systems

Process simulation models and cure monitoring sensors are discussed for use in optimal processing of fiber-reinforced composites. Analytical models relate the specified temperature and pressure cure cycle to the thermal, chemical, and physical processes occurring in the composite during consolidation and cure. Frequency-dependent electromagnetic sensing (FDEMS) is described as an in situ sensor for monitoring the composite curing process and for verification of process simulation models. A model for resin transfer molding of textile composites is used to illustrate the predictive capabilities of a process simulation model. The model is used to calculate the resin infiltration time, fiber volume fraction, resin viscosity, and resin degree of cure. Results of the model are compared with in situ FDEMS measurements.

Loos, Alfred C.

Improving Additive Manufactured Component Performance through Multi-Scale Microstructure Simulation and Process Optimization

The purpose of this project was to utilize computational tools to understand the relationships between processing, microstructure, and properties for additively manufactured (AM) aluminum alloys for automotive applications, and to provide an engineering solution for helping to optimize process conditions. The project leverages ORNL developments in computational modeling, including AM process modeling, phase-field based microstructure evolution predictions, and data analytics techniques for mapping process conditions to material outcomes. The project utilized an Al-Cu-Mn-Zr alloy as a model material for studying formation of defects and microstructural features in response to variations in process conditions. Based on both pre-existing experimental data and simulation results, statistical process maps were constructed to identify regions of process space with minimal defect formation and advantageous microstructures and properties. The software tools used for this purpose were successful disseminated to GM, who were able to successful compile the relevant HPC codes within their own computing ecosystem and perform initial calculations to reproduce ORNL results.

36 MATERIALS SCIENCE

Simulation of Unique Pressure Changing Steps and Situations in Psa Processes

A more rigorous cyclic adsorption process simulator is being developed for use in the development and understanding of new and existing PSA processes. Unique features of this new version of the simulator that Ritter and co-workers have been developing for the past decade or so include: multiple absorbent layers in each bed, pressure drop in the column, valves for entering and exiting flows and predicting real-time pressurization and depressurization rates, ability to account for choked flow conditions, ability to pressurize and depressurize simultaneously from both ends of the columns, ability to equalize between multiple pairs of columns, ability to equalize simultaneously from both ends of pairs of columns, and ability to handle very large pressure ratios and hence velocities associated with deep vacuum systems. These changes to the simulator now provide for unique opportunities to study the effects of novel pressure changing steps and extreme process conditions on the performance of virtually any commercial or developmental PSA process. This presentation will provide an overview of the cyclic adsorption process simulator equations and algorithms used in the new adaptation. It will focus primarily on the novel pressure changing steps and their effects on the performance of a PSA system that epitomizes the extremes of PSA process design and operation. This PSA process is a sorbent-based atmosphere revitalization (SBAR) system that NASA is developing for new manned exploration vehicles. This SBAR system consists of a 2-bed 3-step 3-layer system that operates between atmospheric pressure and the vacuum of space, evacuates from both ends of the column simultaneously, experiences choked flow conditions during pressure changing steps, and experiences a continuously changing feed composition, as it removes metabolic CO2 and H20 from a closed and fixed volume, i.e., the spacecraft cabin. Important process performance indicators of this SBAR system are size, and the corresponding CO2 and H20 removal efficiencies, and N2 and O2 loss rates. Results of the fundamental behavior of this PSA process during extreme operating conditions will be presented and discussed.

Ebner, Armin D.

Characterization of and sensor-model verification and control of the properties of PMR-13 during processing

This study presents an in situ sensor and a process-simulation model developed for monitoring and controlling the cure process of PMR-15. The time-temperature dependence of the buildup in the molecular network structure, extent of reaction, viscosity, flow, and consolidation during the cure of PMR-15 are discussed. The relationship of the time-temperature cycle used during imidization to the length of the endcapped chains formed is examined. The relationship of the time-temperature cure-processing cycle to the reaction kinetics, viscosity, flow, and consolidation during crosslinking is analyzed using frequency-dependent electromagnetic sensors and the Loos processing model. Application of the FDEMS sensing technique and the process-simulation model for quality assurance processing and automated on-line control of cure is discussed.

Kranbuehl, D.

Modeling and simulation: A key to future defense technology

The purpose of this paper is to express the rationale for continued technological and scientific development of the modeling and simulation process for the defense industry. The defense industry, along with a variety of other industries, is currently being forced into making sacrifices in response to the current economic hardships. These sacrifices, which may not compromise the safety of our nation, nor jeopardize our current standing as the world peace officer, must be concentrated in areas which will withstand the needs of the changing world. Therefore, the need for cost effective alternatives of defense issues must be examined. This paper provides support that the modeling and simulation process is an economically feasible process which will ensure our nation's safety as well as provide and keep up with the future technological developments and demands required by the defense industry. The outline of this paper is as follows: introduction, which defines and describes the modeling and simulation process; discussion, which details the purpose and benefits of modeling and simulation and provides specific examples of how the process has been successful; and conclusion, which summarizes the specifics of modeling and simulation of defense issues and lends the support for its continued use in the defense arena.

Muccio, Anthony B.

Detailed Modeling of Distillation Technologies for Closed-Loop Water Recovery Systems

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA?s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents efforts to develop chemical process simulations for three technologies: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system and the Wiped-Film Rotating Disk (WFRD) using the Aspen Custom Modeler and Aspen Plus process simulation tools. The paper discusses system design, modeling details, and modeling results for each technology and presents some comparisons between the model results and recent test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Allada, Rama Kumar

Resimulation-based self-supervised learning for pretraining physics foundation models

Self-supervised learning (SSL) is at the core of training modern large machine learning models, providing a scheme for learning powerful representations that can be used in a variety of downstream tasks. However, SSL strategies must be adapted to the type of training data and downstream tasks required. We propose resimulation-based self-supervised representation learning (RS3L), a novel simulation-based SSL strategy that employs a method of resimulation to drive data augmentation for contrastive learning in the physical sciences, particularly, in fields that rely on stochastic simulators. By intervening in the middle of the simulation process and rerunning simulation components downstream of the intervention, we generate multiple realizations of an event, thus producing a set of augmentations covering all physics-driven variations available in the simulator. Using experiments from high-energy physics, we explore how this strategy may enable the development of a foundation model; we show how RS3L pretraining enables powerful performance in downstream tasks such as discrimination of a variety of objects and uncertainty mitigation. In addition to our results, we make the RS3L dataset publicly available for further studies on how to improve SSL strategies.

97 MATHEMATICS AND COMPUTING

A 3D Model to Predict Explicit Morphologies and Volume Fraction of Lack-of-Fusion Pores Generated in Selective Laser Melting Processes

The performance of an additively manufactured (AM) component is dependent on the distribution of process-induced defects in addition to the complex microstructure of the material, surface roughness of the component and the process-induced residual stresses. For instance, it has been well demonstrated that lack-of-fusion (LoF) pores produced in the selective laser melting (SLM) AM process can significantly limit the fatigue performance of the material. Although two-dimensional (2D) models exist to predict the 2D profiles of LoF pores, the 2D pore profiles cannot be directly inserted into a three-dimensional (3D) microstructure domain that is output from several prevailing process simulation packages. A few commercial packages that simulate the SLM process can predict LoF pores in a 3D domain, but the morphologies of LoF pores are voxelated and hence do not capture sharp corners of the pores, thereby obviating their use in fatigue crack initiation studies. In order to address the aforementioned gaps, a high-fidelity model that predicts not only the volume fraction, but also the explicit 3D morphologies and spatial distributions of LoF pores has been developed using a computer aided design-based environment. The model has been partially validated for Ti-6Al-4V alloy by comparing the predictions of the volume fraction of LoF pores predicted by the model with experimental data obtained from the literature. Absolute error in predicted volume fraction of LoF pores varied between 5.16% and 1.87% for energy density values between 13 J/mm3 and 45 J/mm3 where a significant amount (over 3% volume fraction) of LoF porosity was measured. The absolute error was within 1.87% for energy density values greater than 45 J/mm3.

Saikumar R. Yeratapally

Opportunities and challenges in process modeling and simulation of electrochemical systems

Electrochemical technologies have garnered intense interest in both academic research and industrial applications due to their potential to increase energy efficiency and reduce carbon footprint. However, electrochemical process fundamentals have been absent from the chemical process simulators available to millions of chemical engineers worldwide. To expedite process research and development of electrochemical technologies in the chemical industry, it is imperative that essential electrochemical process fundamentals be incorporated into process simulators to support modeling and simulation of electrochemical processes. Here, this study examines three process fundamentals key to the research and development of electrochemical processes: electrochemical reaction kinetics, electrolyte thermodynamics, and heat and mass transfer. It further illustrates application of these process fundamentals with a case study modeling an electrochemical process for the conversion of acrylonitrile to adiponitrile. The modeling example highlights the roles of applied voltage on reaction rates, and electron flow rates on the performance of electrochemical processes. It suggests that the applied voltage and electron flow rates are two unique concepts that should be included in simulators for electrochemical processes.

09 BIOMASS FUELS