Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “design (process simulation)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Analog Design for Digital Deployment of a Serious Leadership Game

This paper presents the design, development, and user testing of a leadership development simulation. The authors share lessons learned from using a design process for a board game to allow for quick and inexpensive revision cycles during the development of a serious leadership development game. The goal of this leadership simulation is to accelerate the development of leadership capacity in high-potential mid-level managers (GS-15 level) in a federal government agency. Simulation design included a mixed-method needs analysis, using both quantitative and qualitative approaches to determine organizational leadership needs. Eight design iterations were conducted, including three user testing phases. Three re-design iterations followed initial development, enabling game testing as part of comprehensive instructional events. Subsequent design, development and testing processes targeted digital application to a computer- and tablet-based environment. Recommendations include pros and cons of development and learner testing of an initial analog simulation prior to full digital simulation development.

Maxwell, Nicholas↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗
NASA NTRS2003

Science-return modeling and simulation

In this paper, an on-going effort to integrate science-return modeling and simulation with JPL's institutional mission system design process will be presented.

modeling simulation↗
DOE OSTI2017

Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. For multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Comparisons of Kinematics and Dynamics Simulation Software Tools

Kinematic and dynamic analyses for moving bodies are essential to system engineers and designers in the process of design and validations. 3D visualization and motion simulation plus finite element analysis (FEA) give engineers a better way to present ideas and results. Marshall Space Flight Center (MSFC) system engineering researchers are currently using IGRIP from DELMIA Inc. as a kinematic simulation tool for discrete bodies motion simulations. Although IGRIP is an excellent tool for kinematic simulation with some dynamic analysis capabilities in robotic control, explorations of other alternatives with more powerful dynamic analysis and FEA capabilities are necessary. Kinematics analysis will only examine the displacement, velocity, and acceleration of the mechanism without considering effects from masses of components. With dynamic analysis and FEA, effects such as the forces or torques at the joint due to mass and inertia of components can be identified. With keen market competition, ALGOR Mechanical Event Simulation (MES), MSC visualNastran 4D, Unigraphics Motion+, and Pro/MECHANICA were chosen for explorations. In this study, comparisons between software tools were presented in terms of following categories: graphical user interface (GUI), import capability, tutorial availability, ease of use, kinematic simulation capability, dynamic simulation capability, FEA capability, graphical output, technical support, and cost. Propulsion Test Article (PTA) with Fastrac engine model exported from IGRIP and an office chair mechanism were used as examples for simulations.

Yeu-Sheng Paul Shiue↗
NASA NTRS2005

Range Process Simulation Tool

Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.

Phillips, Dave↗
DOE OSTI2014

Human Factors Engineering Design Phase Report for Control Room Modernization

In this report, we review recent work performed at the Human System Simulation Laboratory (HSSL) at the Idaho National Laboratory. The U.S. Department of Energy has sponsored work under the Light Water Reactor Sustainabilty (LWRS) program to assist U.S. utilities in extending the operating life of the U.S. fleet of commercial reactors. Control room modernization is a key research and demonstration area within LWRS. The U.S. Nuclear Regulatory Commission’s Human Factors Engineering Program Review Model (NUREG-0711) outlines four phases of developing a new human-system interface (HSI). One of the key steps in NUREG-0711 is the design phase. In this report, we outline the process and findings from several simulator workshops, which centered on early design phase activities. Prototypes for a turbine control system upgrade for a main control room at a commercial nuclear power plant were developed and evaluated using licensed reactor operators at the HSSL. This iterative design-evaluation cycle succeeded in refining the design of the HSI and readying it for final implementation and formal validation and verification exercises. This report serves as a useful template to explicate design steps that are not currently required by NUREG-0711 but that ensure a usable and safe control room replacement system.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2014

Designing Liquid Rocket Engine Injectors for Performance, Stability, and Cost

NASA is developing the Space Launch System (SLS) for crewed exploration missions beyond low Earth orbit. Marshall Space Flight Center (MSFC) is designing rocket engines for the SLS Advanced Booster (AB) concepts being developed to replace the Shuttle-derived solid rocket boosters. One AB concept uses large, Rocket-Propellant (RP)-fueled engines that pose significant design challenges. The injectors for these engines require high performance and stable operation while still meeting aggressive cost reduction goals for access to space. Historically, combustion stability problems have been a critical issue for such injector designs. Traditional, empirical injector design tools and methodologies, however, lack the ability to reliably predict complex injector dynamics that often lead to combustion stability. Reliance on these tools alone would likely result in an unaffordable test-fail-fix cycle for injector development. Recently at MSFC, a massively parallel computational fluid dynamics (CFD) program was successfully applied in the SLS AB injector design process. High-fidelity reacting flow simulations were conducted for both single-element and seven-element representations of the full-scale injector. Data from the CFD simulations was then used to significantly augment and improve the empirical design tools, resulting in a high-performance, stable injector design.

Westra, Douglas G.↗
NASA NTRS2015

Combining Simulation Tools for End-to-End Trajectory Optimization

Trajectory simulations with advanced optimization algorithms are invaluable tools in the process of designing spacecraft. Due to the need for complex models, simulations are often highly tailored to the needs of the particular program or mission. NASA's Orion and SLS programs are no exception. While independent analyses are valuable to assess individual spacecraft capabilities, a complete end-to-end trajectory from launch to splashdown maximizes potential performance and ensures a continuous solution. In order to obtain end-to-end capability, Orion's in-space tool (Copernicus) was made to interface directly with the SLS's ascent tool (POST2) and a new tool to optimize the full problem by operating both simulations simultaneously was born.

Whitley, Ryan↗
NASA NTRS1978

Synthetic Aperture Radar Technology Conference, New Mexico State University, Las Cruces, N. Mex., March 8-10, 1978, Proceedings

The following aspects of SAR development are discussed: calibration techniques, image simulation and interpretability, antennas, data processing, and system design. Papers are presented on such topics as a postlaunch calibration experiment for the Seasat-A SAR, computer simulation of an orbital SAR system, definition study of the Shuttle Imaging Radar, custom LSI circuits for spaceborne SAR processors, and random sampling adaptively focusing SAR.

Source record↗
NASA NTRS2012

Overcoming the Critical Shortage of STEM - Prepared Secondary Students Through Modeling and Simulation

In developing understanding of technological systems - modeling and simulation tools aid significantly in the learning and visualization processes. In design courses we sketch , extrude, shape, refine and animate with virtual tools in 3D. Final designs are built using a 3D printer. Aspiring architects create spaces with realistic materials and lighting schemes rendered on model surfaces to create breathtaking walk-throughs of virtual spaces. Digital Electronics students design systems that address real-world needs. Designs are simulated in virtual circuits to provide proof of concept before physical construction. This vastly increases students' ability to design and build complex systems. We find students using modeling and simulation in the learning process, assimilate information at a much faster pace and engage more deeply in learning. As Pre-Engineering educators within the Career and Technical Education program at our school division's Technology Academy our task is to help learners in their quest to develop deep understanding of complex technological systems in a variety of engineering disciplines. Today's young learners have vast opportunities to learn with tools that many of us only dreamed about a decade or so ago when we were engaged in engineering and other technical studies. Today's learner paints with a virtual brush - scenes that can aid significantly in the learning and visualization processes. Modeling and simulation systems have become the new standard tool set in the technical classroom [1-5]. Modeling and simulation systems are now applied as feedback loops in the learning environment. Much of the study of behavior change through the use of feedback loops can be attributed to Stanford Psychologist Alfred Bandura. "Drawing on several education experiments involving children, Bandura observed that giving individuals a clear goal and a means to evaluate their progress toward that goal greatly increased the likelihood that they would achieve it."

Spencer, Thomas↗
DOE OSTI2013

Efficient simulation of press hardening process through integrated structural and CFD analyses

Press hardened steel parts are being increasingly used in automotive structures for their higher strength to meet safety standards while reducing vehicle weight to improve fuel consumption. However, manufacturing of sheet metal parts by press hardening process to achieve desired properties is extremely challenging as it involves complex interaction of plastic deformation, metallurgical change, thermal distribution, and fluid flow. Numerical simulation is critical for successful design of the process and to understand the interaction among the numerous process parameters to control the press hardening process in order to consistently achieve desired part properties. Until now there has been no integrated commercial software solution that can efficiently model the complete process from forming of the blank, heat transfer between the blank and tool, microstructure evolution in the blank, heat loss from tool to the fluid that flows through water channels in the tools. In this study, a numerical solution based on Altair HyperWorks® product suite involving RADIOSS®, a non-linear finite element based structural analysis solver and AcuSolve®, an incompressible fluid flow solver based on Galerkin Least Square Finite Element Method have been utilized to develop an efficient solution for complete press hardening process design and analysis. RADIOSS is used to handle the plastic deformation, heat transfer between the blank and tool, and microstructure evolution in the blank during cooling. While AcuSolve is used to efficiently model heat loss from tool to the fluid that flows through water channels in the tools. The approach is demonstrated through some case studies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models

Computer experiments often employ space-filling strategies to create surrogate models with strong predictive performance. The impact of model parameter estimation for Gaussian process surrogates, however, is often overlooked. Obtaining a better initial estimate of the covariance lengthscale parameter, θ, can greatly improve the resulting Gaussian process fit through more effective sequential acquisitions during active learning. In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter. Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process. Our Bayesian D-optimal designs are rooted in information theory and lead to more informative sequential acquisitions by improving lengthscale estimation. In many cases, these gains eventually result in better surrogates than those seeded with space-filling initial designs. Furthermore, Bayesian D-optimal designs can be tailored to either isotropic or anisotropic covariance structures, and the Bayesian framework enables the inclusion of prior knowledge in the design process, offering greater flexibility and adaptability. Through several simulation studies, we demonstrate the advantages of Bayesian D-optimal designs in terms of both lengthscale estimation accuracy and predictive performance during active learning.

Bayesian experimental design↗
DOE OSTI2012

Metrics for Availability Analysis Using a Discrete Event Simulation Method

The system performance metric 'availability' is a central concept with respect to the concerns of a plant's operators and owners, yet it can be abstract enough to resist explanation at system levels. Hence, there is a need for a system-level metric more closely aligned with a plant's (or, more generally, a system's) raison d'etre. Historically, availability of repairable systems - intrinsic, operational, or otherwise - has been defined as a ratio of times. This paper introduces a new concept of availability, called endogenous availability, defined in terms of a ratio of quantities of product yield. Endogenous availability can be evaluated using a discrete event simulation analysis methodology. A simulation example shows that endogenous availability reduces to conventional availability in a simple series system with different processing rates and without intermediate storage capacity, but diverges from conventional availability when storage capacity is progressively increased. It is shown that conventional availability tends to be conservative when a design includes features, such as in - process storage, that partially decouple the components of a larger system.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2003

Rapid Prototyping of an Aircraft Model in an Object-Oriented Simulation

A team was created to participate in the Mars Scout Opportunity. Trade studies determined that an aircraft provided the best opportunity to complete the science objectives of the team. A high fidelity six degree of freedom flight simulation was required to provide credible evidence that the aircraft design fulfilled mission objectives and to support the aircraft design process by providing performance evaluations. The team created the simulation using the Langley Standard Real-Time Simulation in C++ (LaSRS++) application framework. A rapid prototyping approach was necessary because the team had only three months to both develop the aircraft simulation model and evaluate aircraft performance as the design and mission parameters matured. The design of LaSRS++ enabled rapid-prototyping in several ways. First, the framework allowed component models to be designed, implemented, unit-tested, and integrated quickly. Next, the framework provides a highly reusable infrastructure that allowed developers to maximize code reuse while concentrating on aircraft and mission specific features. Finally, the framework reduces risk by providing reusable components that allow developers to build a quality product with a compressed testing cycle that relies heavily on unit testing of new components.

Kenney, P. Sean↗
DOE OSTI2024

A Gaussian process based surrogate approach for the optimization of cylindrical targets

Simulating direct-drive inertial confinement experiments presents significant computational challenges, both due to the complexity of the codes required for such simulations and the substantial computational expense associated with target design studies. Machine learning models, and in particular, surrogate models, offer a solution by replacing simulation results with a simplified approximation. In this study, we apply surrogate modeling and optimization techniques that are well established in the existing literature to one-dimensional simulation data of a new cylindrical target design containing deuterium–tritium fuel. These models predict yields without the need for expensive simulations. We find that Bayesian optimization with Gaussian process surrogates enhances sampling efficiency in low-dimensional design spaces but becomes less efficient as dimensionality increases. Nonetheless, optimization routines within two-dimensional and five-dimensional design spaces can identify designs that maximize yield, while also aligning with established physical intuition. Optimization routines, which ignore constraints on hydrodynamic instability growth, are shown to lead to unstable designs in 2D, resulting in yield loss. However, routines that utilize 1D simulations and impose constraints on the in-flight aspect ratio converge on novel cylindrical target designs that are stable against hydrodynamic instability growth in 2D and achieve high yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2021

I’ll have the Porter: Interactively Visualizing the Results of Statistical Maneuver Analysis

Mission design and navigation relies on statistical maneuver analysis and Monte Carlo simulations when evaluating candidate mission trajectories. Engineers must analyze large quantities of data to optimize mission safety and propellant margins, but currently rely on static text files and dense PDF slide decks to review simulation results. This approach is time-intensive, non-interactive, and difficult to share or coordinate with other mission designers. To improve this process, we present Porter: a web-based interactive mission analysis tool. This work describes Porter’s user-centered design process, its processing pipeline for importing and processing LAMBIC simulation data, core interactive features, and preliminary user feedback.

Ramaswamy, Basak Alper↗