Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “criticality simulations”

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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

NAS Technical Summaries, March 1993 - February 1994

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefitting other supercomputer centers in government and industry. The 1993-94 operational year concluded with 448 high-speed processor projects and 95 parallel projects representing NASA, the Department of Defense, other government agencies, private industry, and universities. This document provides a glimpse at some of the significant scientific results for the year.

Source record↗
NASA NTRS1994

Shortwave feedbacks and El Nino-Southern Oscillation: Forced ocean coupled ocean-atmosphere experiments

Changes in tropical sea surface temperature (SST) can produce changes in cloudiness that modify incoming solar shortwave (SW) radiation, which in turn affects SST. The effects of this negative feedback on Pacific interannual variability are examined in forced ocean model and hybrid coupled ocean-atmosphere model simulations. Two empirical schemes are used to model the large-scale, low-frequency response of surface SW to SST anomalies. The first scheme attempts to account for the nonlocal nature of the atmospheric response to SST based patterns of covariability analyzed through singular value decomposition. In the observations the primary coupled mode of variability is composed of a SW anomaly in the central Pacific that covaries with anomalous SST in the eastern Pacific. This is applied in the model as a nonlocal feedback. The second scheme examines the effects of a purely local feedback with a spatially varying coefficient of magnitude chosen similar to the first scheme. In almost all cases the second scheme behaved similarly to the first, presumably because the correlation scale of SST is large enough for El Nino-Southern Oscillation (ENSO) dynamics that there is little sensitivity to the local approximation in the SW feedback. In simulations forced by time series of observed wind stress the SW feedback induced very minor SST damping. Results for a simpified heat budget analysis showed that while the SW feedback increased the local heat flux damping on SST, it also induced a mean shallowing of the mixed layer. The resulting changes in both the local mean vertical temperature gradient and the zonal velocity response to the wind stress acted to oppose the local heat flux damping effects. When the observed SW anomalies were applied to forced simulations, the simulated SST anomalies were modified as expected, and agreement with observed SST improved. In coupled simulations the SW feedbacks had greater impact than in the case of specified stress. The main effects were to decrease the magnitude of the warm and cold SST anomalies in the central Pacific, while leaving the pattern and evolution of ENSO anomalies essentially unchanged elsewhere. The SW feedbacks thus produce a modest improvement of the model ENSO SST pattern compared with observations, although they tended to shorten the period of the model ENSO cycle. Overall the results suggest that large-scale SW feedbacks are of quantitative importance to simulating some aspects of the ENSO cycle but are not critical to the overall occurrence of the phenomenon.

Waliser, Duane E.↗
NASA NTRS1999

Residual Strength Predictions with Crack Buckling

Fracture tests were conducted on middle crack tension, M(T), and compact tension, C(T), specimens of varying widths, constructed from 0.063 inch thick sheets of 2024-T3 aluminum alloy. Guide plates were used to restrict out-of-plane displacements in about half of the tests. Analyses using the three-dimensional, elastic-plastic finite element code WARP3D simulated the tests with and without guide plates using a critical CTOA fracture criterion. The experimental results indicate that crack buckling reduced the failure loads by up to 40%. Using a critical CTOA value of 5.5 deg., the WARP3D analyses predicted the failure loads for the tests with guide plates within +/- 10% of the experimentally measured values. For the M(T) tests without guide plates, the WARP3D analyses predicted the failure loads for the 12 and 24 inch tests within 10%, while over predicting the failure loads for the 40 inch wide tests by about 20%.

Dawicke, D. S.↗
NASA NTRS1999

The Numerical Propulsion System Simulation: A Multidisciplinary Design System for Aerospace Vehicles

Advances in computational technology and in physics-based modeling are making large scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze ma or propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of design process and to provide the designer with critical information about the components early in the design process. This paper describes the development of the Numerical Propulsion System Simulation (NPSS), a multidisciplinary system of analysis tools that is focussed on extending the simulation capability from components to the full system. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lytle, John K.↗
NASA NTRS2000

Leonid Shower Probe of Aerothermochemistry in Meteoric Plasmas and Implication for the Origin of Life

The rarefied and high Mach number (up to 270) of the flow field of a typical meteoroid as it enters the Earth's atmosphere implies conditions of ablation and atmospheric chemistry that have proven to be as difficult to grasp as the proverbial shooting star. An airborne campaign was organized to study these processes during an intense Leonid shower. A probe of molecular band emission now demonstrates that the flash of light from a common meteor originates in the wake of the object rather than in the meteor head. A new theoretical approach using the direct simulation Monte Carlo technique demonstrates that the ablation process is critical in heating the air in that wake. Air molecules impinge on a dense cloud of ablated material in front of the meteoroid head into an extended wake that has the observed excitation temperatures. These processes determine what extraterrestrial materials may have been delivered to Earth at the time of the origin of life.

Jenniskens, Peter S. I.↗
NASA NTRS2005

Mitigating Motion Base Safety Issues: The NASA LaRC CMF Implementation

The NASA Langley Research Center (LaRC), Cockpit Motion Facility (CMF) motion base design has taken advantage of inherent hydraulic characteristics to implement safety features using hardware solutions only. Motion system safety has always been a concern and its implementation is addressed differently by each organization. Some approaches rely heavily on software safety features. Software which performs safety functions is subject to more scrutiny making its approval, modification, and development time consuming and expensive. The NASA LaRC's CMF motion system is used for research and, as such, requires that the software be updated or modified frequently. The CMF's customers need the ability to update the simulation software frequently without the associated cost incurred with safety critical software. This paper describes the CMF engineering team's approach to achieving motion base safety by designing and implementing all safety features in hardware, resulting in applications software (including motion cueing and actuator dynamic control) being completely independent of the safety devices. This allows the CMF safety systems to remain intact and unaffected by frequent research system modifications.

Bryant, Richard B., Jr.↗
NASA NTRS2013

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.

land-surface modeling↗
NASA NTRS2017

Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

Warner, James E.↗
NASA NTRSDate not supplied

Microservice Architecture for Cognitive Networks

This develops the concept of a cognitive network and describes a microservice based architecture which could be used to implement such a system. Delay tolerant networking (DTN) influences the design of the architecture as well as the networking scenarios that the system attempts to address. A cognitive storage and fragmentation service is developed based on existing artificial intelligence techniques such as Advantage Actor Critic (A2C) and Deep Q-Networks. The system is simulated using OpenAI Gym in a custom developed DTN environment.

cognitive networks↗
NASA NTRSDate not supplied

SERFE Water Quality Results

NASA has been developing a new spacesuit, called the Exploration Extravehicular Mobility Unit (xEMU) for over a decade. This spacesuit is underdevelopment to support missions to the International Space Station (ISS) and also to the Moon. Improvements in the life and robustness of the Portable Life Support System (PLSS) has been a major objective of these efforts. Water quality, and how that impacts the performance of the life support system hardware, are areas where improvements could greatly help to achieve these goals. The Suit Water Membrane Evaporator (SWME) was chosen as the technology to provide cooling to the xEMU and has undergone several iterations of development over this period. An ISS flight experiment centered around the SWME and other thermal loop technologies was developed and has been under test in an ISS EXpedite PRocessing of Experiments to the Space Station (EXPRESS) rack since November of 2020. In addition to the SWME, The SWME EXPRESS Rack Flight Experiment (SERFE) contains several technology demonstrations from the xEMU project and has been demonstrating their performance in micro-gravity and over an extended duration. This paper will summarize the results of the water quality analysis performed to date throughout the SERFE testing program. Special care was taken to select materials, process hardware, and control the quality of the feedwater used in SERFE testing so that it would be representative of a thermal control system that could be used on a spacesuit for a lunar mission. In addition, the testing schedule, including periods of quiescence in between tests, was also selected to simulate a real mission profile in ways that would be critical to water quality. Results include data and analysis on microbial activity, biocidal iodine, metals, organic carbon, and several other customary indicators of water quality in an operational system. Testing spans over a year and a half of wetted life of the SERFE Flight Unit and the SERFE Ground Unit.

Colin Campbell↗
NASA NTRS2023

Utilizing Code Generation from Models for Electric Aircraft Motor Controller Flight Software

The processes followed to develop and test safety-critical flight software significantly increase development effort and overhead in comparison to both non-safety-critical and non-flight software. Generating code from models can be used to reduce development effort; however, the processes for using code generation to develop flight software are relatively immature. This work presents an approach for developing safety-critical flight software utilizing code generation from models to reduce development time and effort. The presented use-case is of electric aircraft motor control software developed for NASA's X-57 Maxwell aircraft.

flight software↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
DOE OSTI2025

NE-COST plug-in: Expanding ACCERT's Capabilities for Life-Cycle Cost Modeling

The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.

Zhou, Jia↗
DOE OSTI2025

High-Resolution Simulations of Geological CO 2 Injection: Application to the SPE11 Benchmark

Geological carbon sequestration (GCS) will play a critical role in decarbonization and in facilitating the transition to clean energy systems. Because CO 2 is highly mobile, ensuring its safe and permanent injection into subsurface geological formations involves monitoring over larger spatial domains and longer time periods than is typical for hydrocarbon reservoirs. This can benefit from simulation tools capable of modeling key CO 2 trapping mechanisms, particularly those optimized for speed and scalability on high-performance computing systems. Using isothermal versions of the SPE11B and SPE11C benchmark cases, we conduct a mesh refinement study simulating CO 2 injection into kilometer-scale rock formations at centimeter resolution with the GEOS open-source simulation framework. We focus on how mesh refinement improves the accuracy of convective mixing in both 2D and 3D simulations. The computational costs associated with achieving a converged solution highlight the need for predictive upscaling techniques. A systematic performance scaling analysis—including both central processing unit (CPU) and graphics processing unit (GPU) architectures—complements the “Results” section.

Geosciences↗
DOE OSTI2025

A general kinetic framework for dislocation mobility derived from probabilistic cellular automaton simulations of the kink-pair mechanism

Dislocation mobility laws are essential components of dislocation-density-based crystal plasticity models. For dislocations governed by the kink-pair mechanism, however, existing formulations are typically limited to specific regimes due to the com plex interplay between stochastic kink-pair nucleation and lateral kink migration. In this work, we develop a general kinetic framework that expresses the average dislocation velocity as a function of mechanism-level variables: positive/negative kink pair nucleation rates, kink migration velocity, dislocation segment length, critical kink-pair width, and kink height. Probabilis tic cellular automaton simulations are used to capture the behavior of conceptual dislocation segments between the limiting conditions of migration outpacing nucleation on the one end and nucleation outpacing migration on the other. An elemen tary functional form that captures the system dynamics is suggested and fitted against the simulation results. This framework remains valid for arbitrary combinations of the six variables and is, therefore, compatible with any admissible constitutive re lations that describe their stress and temperature dependence. Comparisons with established approaches and experimental results confirm the robustness and physical consistency of the formulation, making it broadly applicable to material systems in which dislocation motion is governed by the kink-pair mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of Surface Crack Formation in Photovoltaic Backsheets Using Fragmentation and Finite Element Simulations: Preprint

Backsheet cracking is among the most commonly observed degradation modes of photovoltaic (PV) modules in the field. Cracks can reduce the ability of backsheets to fulfil their functions, for example, protection of the modules from the environment or electrical insulation. This work presents an evaluation of the degradation and cracking propensity of two backsheets during accelerated IEC TS 62788-7-2 A3 (International Electrotechnical Commission) aging with the fragmentation test: a co-extruded polyamide backsheet (AAA), and a laminated multilayer backsheet with a polyethylene terephthalate core and outer layer and ethylene vinyl acetate inner layer (PPE). Results show the surface embrittlement of the AAA outer layer during exposure. A longer time of exposure causes cracks to form at lower strains during stretching and creates deeper cracks. Accordingly, Young's modulus of the outer layer increases, as measured by cross-sectional nanoindentation. PPE exhibits cracking after exposure as well. While no similar increase of modulus or crack depth can be observed, the outer layer of PPE exhibits more obvious signs of erosion during exposure, including progressive morphological changes and thickness losses. A finite element model to simulate surface crack formation is devised, based on initially zero-thickness decohesion elements. Decohesion criteria define a critical stress, at which these elements grow, and cracks can begin to form. These criteria are obtained via parameter optimization by comparison between simulation and experiment. The model is used to interpret crack formation in both backsheets.

backsheet↗
DOE OSTI2025

High order interpolation of magnetic fields with vector potential reconstruction for particle simulations

We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincaré section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Lastly, we demonstrate performant Poincaré section analysis in two relevant settings of field data collocated from finite element meshes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗