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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Flow behavior in liquid molding

The liquid molding (LM) process for manufacturing polymer composites with structural properties has the potential to significantly lower fabrication costs and increase production rates. LM includes both resin transfer molding and structural reaction injection molding. To achieve this potential, however, the underlying science base must be improved to facilitate effective process optimization and implementation of on-line process control. The National Institute of Standards and Technology (NIST) has a major program in LM that includes materials characterization, process simulation models, on-line process monitoring and control, and the fabrication of test specimens. The results of this program are applied to real parts through cooperative projects with industry. The key feature in the effort is a comprehensive and integrated approach to the processing science aspects of LM. This paper briefly outlines the NIST program and uses several examples to illustrate the work.

Hunston, D.↗
DOE OSTI2025

Transformational Sorbent-Based Process for a Substantial Reduction in the Cost of CO2 Capture

Adsorption processes have the potential to significantly reduce the CO2 capture cost from power plants and industrial flue gases. InnoSepra has developed several sorbent-based technologies to obtain very high CO2 recovery and high purity CO2 while meeting the EOR/sequestration product specifications. A first-generation process was shown to achieve CO2 recoveries greater than 94% at CO2 purities in the range of 98.5-99.5%. The absolute heat energy required for the process was not only 40% lower than MEA but also was needed at a much lower temperature. This work will present the performance of the second-generation InnoSepra process which is based on a breakthrough sorbent regeneration method. This process has a projected 45% lower capital cost compared to MEA, less than 16% loss in plant output for CO2 capture and compression, and a CO2 capture cost at least 55% lower than MEA. Lab scale testing and the process simulations indicate a CO2 capture performance similar to or better than the first-generation process. Pilot scale drying and breakthrough tests were carried out at the Technology Centre Mongstad (TCM), Norway, and lab-scale cyclic tests were carried out at InnoSepra to confirm the process improvement. During these tests, InnoSepra’s flue gas purification technology was also tested at TCM. It can provide a low-cost option for the removal of NO2 and SOX to sub-ppm levels as well as a significant reduction in aerosol emissions.

08 HYDROGEN↗
NASA NTRS1989

RTM user's guide

RTM is a FORTRAN '77 computer code which simulates the infiltration of textile reinforcements and the kinetics of thermosetting polymer resin systems. The computer code is based on the process simulation model developed by the author. The compaction of dry, woven textile composites is simulated to describe the increase in fiber volume fraction with increasing compaction pressure. Infiltration is assumed to follow D'Arcy's law for Newtonian viscous fluids. The chemical changes which occur in the resin during processing are simulated with a thermo-kinetics model. The computer code is discussed on the basis of the required input data, output files and some comments on how to interpret the results. An example problem is solved and a complete listing is included.

Claus, Steven J.↗
NASA NTRS2002

Effects of Amine and Anhydride Curing Agents on the VARTM Matrix Processing Properties

To ensure successful application of composite structure for aerospace vehicles, it is necessary to develop material systems that meet a variety of requirements. The industry has recently developed a number of low-viscosity epoxy resins to meet the processing requirements associated with vacuum assisted resin transfer molding (VARTM) of aerospace components. The curing kinetics and viscosity of two of these resins, an amine-cured epoxy system, Applied Poleramic, Inc. VR-56-4 1, and an anhydride-cured epoxy system, A.T.A.R.D. Laboratories SI-ZG-5A, have been characterized for application in the VARTM process. Simulations were carried out using the process model, COMPRO, to examine heat transfer, curing kinetics and viscosity for different panel thicknesses and cure cycles. Results of these simulations indicate that the two resins have significantly different curing behaviors and flow characteristics.

Brian W Grimsley↗
NASA NTRS2016

Composite Cure Process Modeling and Simulations using COMPRO(Registered Trademark) and Validation of Residual Strains using Fiber Optics Sensors

Composite cure process induced residual strains and warping deformations in composite components present significant challenges in the manufacturing of advanced composite structure. As a part of the Manufacturing Process and Simulation initiative of the NASA Advanced Composite Project (ACP), research is being conducted on the composite cure process by developing an understanding of the fundamental mechanisms by which the process induced factors influence the residual responses. In this regard, analytical studies have been conducted on the cure process modeling of composite structural parts with varied physical, thermal, and resin flow process characteristics. The cure process simulation results were analyzed to interpret the cure response predictions based on the underlying physics incorporated into the modeling tool. In the cure-kinetic analysis, the model predictions on the degree of cure, resin viscosity and modulus were interpreted with reference to the temperature distribution in the composite panel part and tool setup during autoclave or hot-press curing cycles. In the fiber-bed compaction simulation, the pore pressure and resin flow velocity in the porous media models, and the compaction strain responses under applied pressure were studied to interpret the fiber volume fraction distribution predictions. In the structural simulation, the effect of temperature on the resin and ply modulus, and thermal coefficient changes during curing on predicted mechanical strains and chemical cure shrinkage strains were studied to understand the residual strains and stress response predictions. In addition to computational analysis, experimental studies were conducted to measure strains during the curing of laminated panels by means of optical fiber Bragg grating sensors (FBGs) embedded in the resin impregnated panels. The residual strain measurements from laboratory tests were then compared with the analytical model predictions. The paper describes the cure process procedures and residual strain predications, and discusses pertinent experimental results from the validation studies.

Sreekantamurthy, Thammaiah↗
DOE OSTI2022

Physics-informed machine learning modeling for predictive control using noisy data

Due to the occurrence of over-fitting at the learning phase, the modeling of chemical processes via artificial neural networks (ANN) by using corrupted data (i.e., noisy data) is an ongoing challenge. Therefore, this work investigates the effect of both Gaussian and non-Gaussian noise on the performance of process-structure based recurrent neural networks (RNN) models, which take the form of partially-connected RNN models in this work, that are used to approximate a class of multi-input-multi-outputs nonlinear systems. Furthermore, two different techniques, specifically Monte Carlo dropout and co-teaching, are utilized in the development of partially-connected RNN models. Here, these two techniques are employed to reduce the over-fitting in ANNs when noisy data is used in the training process and, hence, to improve the open-loop accuracy as well as the closed-loop performance under a Lyapunov-based model predictive controller (MPC). Aspen Plus Dynamics, a well-known high-fidelity process simulator, is used to simulate a large-scale chemical process application in order to demonstrate the anticipated improvements in both open-loop approximation and closed-loop controller performance in the presence of Gaussian and non-Gaussian noise in the data set using physics-informed RNNs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Matrix Characterization and Development for the Vacuum Assisted Resin Transfer Molding Process

The curing kinetics and viscosity of an epoxy resin system, SI-ZG-5A, have been characterized for application in the vacuum assisted resin transfer molding (VARTM) process. Impregnation of a typical carbon fiber perform provided the test bed for the characterization. Process simulations were carried out using the process model, COMPRO, to examine heat transfer and curing kinetics for a fully impregnated panel, neglecting resin flow. The predicted viscosity profile and final degree of cure were found to be in good agreement with experimental observations.

Grimsley, B. W.↗
DOE OSTI2023

MOSCATO Development and Integration in Fiscal Year 2023

In FY23, significant developments were made to the MOSCATO code package, enhancing its capabilities in many aspects. The improvements and advancements can be summarized as follows: Code Restructuring: The MOSCATO code underwent a restructuring process, enabling both Nek5000 and NekRS to share the same interface when using MOSCATO. This integration facilitates smoother interactions between the different modules and streamlines the overall simulation process. Automatic Domain Extension: To allow simulations to propagate over longer time frames, an automatic domain extension capability was added to the metal diffusion module. This enhancement enables more accurate and reliable simulations of diffusion processes, especially in scenarios with extended time requirements. Expanded Corrosion Reactions: The updated MOSCATO package now includes additional reactions that contribute to corrosion. This addition enhances the code’s ability to model corrosion effects more comprehensively, providing a more realistic representation of the systems being studied. Example Case Setup: To assist users and showcase MOSCATO’s capabilities, we developed example cases for various applications. Notably, we created example cases for thermal cells and corrosion loops. These pre-configured cases allow users to get started quickly and effectively with their simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Simulations of Events for the LUX-ZEPLIN (LZ) Dark Matter Experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1–2) ×10−12 pb at a WIMP mass of 40 GeV/ c 2 . This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective

We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. Furthermore, we discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Report of the Electrodynamic Interactions Panel

A wide range of opportunities is provided by the electrodynamic tether to more fully understand the generation of waves in plasmas, the behavior of field aligned currents, the behavior of large body-space plasma interactions, and for process simulation, using the electrodynamic tether to study processes and phenomena relevant to solar system and astrophysics plasma physics. The electrodynamic tether offers a means of study and experimentation in space which will provide a rich yield in new scientific results and will enhance the understanding of space plasma physics. It also has promising technological applications (e.g., the generation of electrical power and thrust) which may be highly significant to future space operations.

Stone, N. H.↗
NASA NTRS2015

Improved Dynamic Modeling of the Cascade Distillation Subsystem and Analysis of Factors Affecting Its Performance

The Cascade Distillation Subsystem (CDS) is a rotary multistage distiller being developed to serve as the primary processor for wastewater recovery during long-duration space missions. The CDS could be integrated with a system similar to the International Space Station Water Processor Assembly to form a complete water recovery system for future missions. A preliminary chemical process simulation was previously developed using Aspen Custom Modeler® (ACM), but it could not simulate thermal startup and lacked detailed analysis of several key internal processes, including heat transfer between stages. This paper describes modifications to the ACM simulation of the CDS that improve its capabilities and the accuracy of its predictions. Notably, the modified version can be used to model thermal startup and predicts the total energy consumption of the CDS. The simulation has been validated for both NaC1 solution and pretreated urine feeds and no longer requires retuning when operating parameters change. The simulation was also used to predict how internal processes and operating conditions of the CDS affect its performance. In particular, it is shown that the coefficient of performance of the thermoelectric heat pump used to provide heating and cooling for the CDS is the largest factor in determining CDS efficiency. Intrastage heat transfer affects CDS performance indirectly through effects on the coefficient of performance.

Perry, Bruce A.↗
DOE OSTI2024

LHC EFT WG note: SMEFT predictions, event reweighting, and simulation

This note provides a comprehensive overview of tools for predicting observables in the Standard Model effective field theory (SMEFT) at both tree level and one loop using event generators. We evaluate three primary methodologies–event reweighting, separate simulation of squared matrix elements, and full SMEFT process simulation–focusing on their statistical performance, computational efficiency, and potential biases. Each approach is assessed in terms of its accuracy, highlighting trade-offs between precision and resource demands. Practical insights into their applicability for high-energy physics analyses are offered, with particular attention to processes where SMEFT effects are significant. Additionally, we discuss the role of helicity in reweighting strategies and its impact on the quality of predictions. By comparing the methods across various LHC processes, this note provides guidance for selecting the most effective strategy for various SMEFT studies, ensuring robust predictions while optimizing computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Performance of hydrophobic physical solvents for pre-combustion CO 2 capture at a pilot scale coal gasification facility

Here, in this paper, we present the first pilot plant data for hydrophobic physical solvents for CO 2 and H 2 S removal from coal-derived H 2 -rich syngas. Four physical solvents were tested under pre-combustion CO 2 capture conditions at bench scale and pilot plant scale: one baseline hydrophilic solvent and three hydrophobic solvents. The solvents were: (1) polyethylene-glycol-dimethyl ether (PEGDME), a hydrophilic solvent analog for the commercial process Selexol, (2) tributyl- phosphate (TBP), a commercially available hydrophobic solvent, (3) polyethylene glycol-poly(dimethylsiloxane) (PEG-PDMS-3), and (4) diethyl sebacate (CASSH-1), a novel, computationally screened hydrophobic solvent developed by the National Energy Technology Laboratory (NETL). All solvents were studied under pure gas (CO 2 /N 2 /H 2 /CH 4 ) equilibrium conditions at NETL followed by pilot plant testing with syngas at the University of North Dakota Energy & Environmental Research Center (UND EERC). Long term performance of CASSH-1 and PEDGME was then assessed with results compared to process simulation predictions. Within experimental uncertainties, all solvents showed comparable CO 2 absorption performance at above room temperature operation while the hydrophobic solvents had limited water uptake and low vapor pressure, which alleviates concerns related to corrosion, water absorption, and solvent loss to evaporation. These results indicate low viscosity, low vapor pressure hydrophobic solvents are a promising option for lower cost CO 2 capture from high pressure syngas applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Identifying impacts of contact tracing on HIV epidemiological inference from phylogenetic data

Abstract Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007–2008 Swedish HIV-1 outbreak and the broader 1998–2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at https://github.com/MolEvolEpid/SEEPS.

Virology↗
DOE OSTI2020

Development of PFLOTRAN Transport Capability for Use in the Waste Isolation Pilot Plant Performance Assessment - 20545

Waste Isolation Pilot Plant (WIPP) performance assessment (PA) calculations estimate the probability of radionuclide release from the repository to the land surface and across the land withdrawal boundary for a regulatory period of 10,000 years after facility closure. Simulations of flow and transport in the repository and the surrounding Salado Formation are foundational to the PA. Because proposed additional waste emplacement panels would result in an asymmetric repository layout, the US Department of Energy (DOE) is preparing to transition to use of a three-dimensional (3-D) model domain for simulation of flow and transport instead of the two-dimensional (2-D) flared grid domain currently used. DOE has charged Sandia National Laboratories with developing the capability necessary to simulate processes affecting flow and transport in the WIPP in PFLOTRAN, an open-source massively parallel multi-phase flow and reactive transport code. The new flow and transport capabilities developed in PFLOTRAN incorporate WIPP-specific process models and will replace the 2-D simulators (BRAGFLO and NUTS) that are currently utilized for Salado flow and transport calculations in WIPP PA. The focus of this paper is on the development of a new Nuclear Waste Transport (NWT) mode in PFLOTRAN that has all of the capabilities necessary for Salado transport simulations, including the ability to handle complete dry-out (100% gas saturation) of arbitrary cells in the model domain, radionuclide mass conservation at step changes in porosity associated with borehole intrusion, and the ability to calculate fluxes on a flared grid. The new PFLOTRAN transport capability and a suite of verification tests were designed around a list of functional requirements for WIPP PA calculations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

42 ENGINEERING↗