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Results for “simulation-based optimization”

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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Improving Discrete-Sensitivity-Based Approach for Practical Design Optimization

In developing the automated methodologies for simulation-based optimal shape designs, their accuracy, efficiency and practicality are the defining factors to their success. To that end, four recent improvements to the building blocks of such a methodology, intended for more practical design optimization, have been reported. First, in addition to a polynomial-based parameterization, a partial differential equation (PDE) based parameterization was shown to be a practical tool for a number of reasons. Second, an alternative has been incorporated to one of the tedious phases of developing such a methodology, namely, the automatic differentiation of the computer code for the flow analysis in order to generate the sensitivities. Third, by extending the methodology for the thin-layer Navier-Stokes (TLNS) based flow simulations, the more accurate flow physics was made available. However, the computer storage requirement for a shape optimization of a practical configuration with the -fidelity simulations (TLNS and dense-grid based simulations), required substantial computational resources. Therefore, the final improvement reported herein responded to this point by including the alternating-direct-implicit (ADI) based system solver as an alternative to the preconditioned biconjugate (PbCG) and other direct solvers.

Baysal, Oktay↗
NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗
NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗
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↗
NASA NTRS2020

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates.As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.

Verification and Validation↗
NASA NTRSDate not supplied

Statistical Wind-Tunnel Experimentation Advancements for eVTOL Aircraft Aero-Propulsive Model Development

Compared to many conventional aircraft, electric vertical takeoff and landing (eVTOL) vehicle designs present greater aero-propulsive complexity and many interacting factors requiring development of novel testing and model development strategies. This paper describes several advances in statistically-rigorous experiment design methods for wind-tunnel testing of eVTOL aircraft enabling accurate aero-propulsive model development. The techniques are applied to a subscale tilt-rotor eVTOL aircraft configuration built at NASA Langley Research Center that has 24 independent control effectors. The general testing approach, leveraging design of experiments and response surface methodology, is outlined and followed by a detailed description of the experiment design and modeling approach employed for different phases of the wind-tunnel testing. A new approach for gravitational tare modeling is developed and validated, which reduces the required wind-tunnel test time by nearly 50%. A mostly automated trim envelope determination approach is formulated to rapidly determine the aircraft flight envelope to inform transition testing for aero-propulsive model development. Efficient powered-airframe characterization tests are conducted using a nested I-optimal design approach formulated in previous simulation-based testing. The collective wind-tunnel testing approach facilitates rapid characterization of eVTOL aircraft configurations and produces accurate aero-propulsive models that can be used in flight dynamics simulations.

design of experiments↗
NASA NTRS2018

Differential Adaptive Stress Testing of Airborne Collision Avoidance Systems

The next-generation Airborne Collision Avoidance System (ACAS X) is currently being developed and tested to replace the Traffic Alert and Collision Avoidance System (TCAS) as the next international standard for collision avoidance. To validate the safety of the system, stress testing in simulation is one of several approaches for analyzing near mid-air collisions (NMACs). Understanding how NMACs can occur is important for characterizing risk and informingdevelopment of the system. Recently, adaptive stress testing (AST) has been proposed as a way to find the most likely path to a failure event. The simulation-based approach accelerates search by formulating stress testing as a sequential decision process then optimizing it using reinforcement learning. The approach has been successfully applied to stress test a prototype of ACAS Xin various simulated aircraft encounters. In some applications, we are not as interestedin the system's absolute performance as its performance relative to another system. Such situations arise, for example, during regression testing or when deciding whether a new system should replace an existing system. In our collision avoidance application, we are interested in finding cases where ACAS X fails but TCAS succeeds in resolving a conflict. Existing approaches do not provide an efficient means to perform this type of analysis. This paper extends the AST approach to differential analysis by searching two simulators simultaneously and maximizing the difference between their outcomes. We call this approach differential adaptive stress testing (DAST). We apply DAST to compare a prototype of ACAS X against TCAS and show examples of encounters found by the algorithm.

Lee, Ritchie↗
NASA NTRS2019

A Multi-Physics Study on High-Specific Power Li-O2 Batteries for Electric Aircraft

Commercialization of lithium-air batteries faces many challenges, such as electrolyte decomposition, short cycle life, low energy and power density, etc. However, commercialization of Li-O2 batteries for aeronautics is much more challenging due to additional safety constraints on cyclability and performance (high specific power and specific energy). For this presentation, we will discuss inter-related aspects of physics-based modeling of a pack: cell and battery model calibration. In addition, we will evaluate and present optimal battery designs for high discharge current density, high discharge time, and low battery mass using simulation-based optimization.The Finite Element Model (FEM) used to simulate a Li-O2 cell is based on the work of Bevara [1]. The different aspects of the model are based on: porous electrode theory and concentrated electrolyte theory; quantum tunneling model for the resistance of conformal layer of discharge product (Li2O2) [1]; Butler-Volmer kinetics for electrochemical reaction; Fick's diffusion for oxygen transport; and an oxygen dissolution model is applied at the air/electrolyte interface [2]. The electrolyte properties such as ion conductivity, ion diffusion, oxygen diffusion, and mass density of the electrolyte were taken from Molecular Dynamics (MD) simulations [3]; while the other model parameters, which includes mass of cell components, were calibrated to match experiments at high discharge current densities. The cell mass includes the anode, cathode, separator, electrolyte, and other components (such as current collector). This calibrated model is used to perform parametric studies on cathode thickness, porosity, tortuosity, carbon particle size, electrolyte transport and material properties, partial pressure of oxygen, discharge time, and discharge current density to study optimal designs for high specific power and energy. References:1. Bevara, V. & Andrei, P. (2014), J. Electrochem. Soc. 161 (14), A2068-A2079.2.Mehta, M. & Andrei, P. (2015), J. Power Sources. 286, 299-308.3.Liyana-Arachchi, T.; Haskins, J.; Burke, C.; Diederichsen, K.; McCloskey, B.; & Lawson, J. (2018), J. Phys. Chem. B. 122 (36), 8548 - 8559.4.Choi, W.; Kikumoto, H.; Choudhary, R. & Ooka, R. (2018), Applied Energy, 209, 306-321.

Mehta, Mohit↗
NASA NTRSDate not supplied

Airburst & Blast Damage Modeling Sensitivities for Asteroid Impact Risk Assessment

Blast overpressure from a high-energy airburst or surface impact is the primary source of damage from potentially hazardous asteroid strikes. There are many sources of uncertainty in evaluating these potential damage risks, both in the approaches used to model the entry, breakup, and airburst behaviors of diverse asteroid properties, and in the blast modeling approaches used to estimate the ground damage from these very large-scale, high-energy events. In this study, we use NASA’s Probabilistic Asteroid Impact Risk (PAIR) model to investigate trends and sensitivities in asteroid airburst altitudes and the resulting blast damage estimates across a range of asteroid sizes. In particular, we show how uncertainties in asteroid breakup behavior and effective airburst altitudes combine with height-of-burst (HOB) blast damage models to produce key sensitivities and trends in the amount of damage expected from different asteroid sizes and airburst altitudes. We show airburst altitude ranges and probabilities stemming from asteroid entry and breakup modeling uncertainties, compare differences between traditional nuclear-based HOB blast models and simulation-based HOB models for larger asteroid energies, and show how the resulting interplay between likely burst altitudes and optimal burst heights affects blast damage trends across different asteroid sizes. Finally, we combine the relative likelihoods of asteroid sizes, airburst altitudes, and resulting blast damage severity to evaluate what airburst regimes pose the highest overall level of risk (when considering both the relative likelihood and scale of potential damage) for a mid-sized asteroid threat scenario. Results show what asteroid size regimes are most sensitive to airburst and blast modeling uncertainties, provide insight into nonintuitive trends in the size and severity of blast damage expected from different airburst events, and highlight where additional blast modeling studies or refinements may help improve future impact risk estimates

ATAP↗
NASA NTRS2010

An Interactive Preliminary Design System of High Speed Forebody and Inlet Flows

This paper demonstrates a simulation-based aerodynamic design process of high speed inlet. A genetic algorithm is integrated into the design process to facilitate the single objective optimization. The objective function is the total pressure recovery and is obtained by using a PNS solver for its computing efficiency. The system developed uses existing software of geometry definition, mesh generation and CFD analysis. The process which produces increasingly desirable design in each genetic evolution over many generations is automatically carried out. A generic two-dimensional inlet is created as a showcase to demonstrate the capabilities of this tool. A parameterized study of geometric shape and size of the showcase is also presented.

Liou, May-Fun↗
NASA NTRS2000

Modeling and Characterization of Geometric Effects on the Performance of Rainbow and Thunder Actuators

Dome formation in Rainbow and Thunder actuators occurs to relieve thermal expansion mismatch stress between the metallic and piezoelectric layers during cooling from device fabrication temperatures. Accompanying this process is the generation of an internal stress profile within the devices and the development of significant tensile stresses within the surface region of the piezoelectric. These tensile stresses affect the domain configuration (ratio of c-to-a domains), and improve the 90 deg. domain wall movement response of the device in this region of the piezoelectric. This results in improved electromechanical performance compared to standard direct extensional and flextensional devices, presumably because of the contributions of stress to the non-linearity of the piezoelectric d-coefficients. 1 Interestingly, this improvement in response seems counterintuitive; a stress perpendicular to the direction of the applied electric field should impede, not contribute to 90' domain switching. Further consideration of the lower region of the piezoelectric that is under compressive stress thus appears warranted. The specified objectives of the research were to: 1. Conduct finite element and equivalent circuit simulation-based investigations to understand the effects of actuator geometry on internal stress distribution and actuator performance (displacement and load-bearing capabilities). 2. Use the results of the modeling studies to predict the processing conditions (geometry and thickness ratio) required for the fabrication of Rainbow ceramics with optimized performance.

Schwartz, Robert W.↗
NASA NTRS2002

Remote Sensing System Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properites such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization, and band-to-band registration drive sensor platform and spaceraft system architecture and cost, analysis of these criteria is important to objectively optimize system design. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy, and geopositional accuracy affect the complexity and cost of calibration methods. However, there are few studies that quantify the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated data sets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution, and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood. This paper describes the ART and its applicability for rigorously deriving remote sensing data requirements.

Zanoni, Vicki↗
NASA NTRS2002

Remote Sensing Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properties such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization and band-to-band registration drive sensor platform and spacecraft system architecture and cost, analysis of these criteria is important to optimize system design objectively. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy and geopositional accuracy affect the complexity and cost of calibration methods. However, few studies have quantified the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at the John C. Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated datasets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood.

Zanoni, Vicki↗
NASA NTRS2021

Computational Inference of Vibratory System with Incomplete Modal Information Using Parallel, Interactive and Adaptive Markov Chains

Inverse analysis of vibratory system is an important subject in fault identification, model updating, and robust design and control. It is challenging subject because 1) the problem is oftentimes underdetermined while the measurements are limited and/or incomplete; 2) many combinations of parameters may yield results that are similar with respect to actual response measurements; and 3) uncertainties inevitably exist. The aim of this research is to leverage upon computational intelligence through statistical inference to facilitate an enhanced, probabilistic framework using incomplete modal response measurement. This new framework is built upon efficient inverse identification through optimization, whereas Bayesian inference is employed to account for the effect of uncertainties. To overcome the computational cost barrier, we adopt Markov chain Monte Carlo (MCMC) to characterize the target function/distribution. Instead of using single Markov chain in conventional Bayesian approach, we develop a new sampling theory with multiple parallel, interactive and adaptive Markov chains and incorporate it into Bayesian inference. This can harness the collective power of these Markov chains to realize the concurrent search of multiple local optima. The number of required Markov chains and their respective initial model parameters are automatically determined via Monte Carlo simulation-based sample pre-screening followed by K-means clustering analysis. These enhancements can effectively address the aforementioned challenges in finite element inverse analysis. The validity of this framework is systematically demonstrated through case studies.

K Zhou↗
NASA NTRS2014

Traffic Aware Planner (TAP) Flight Evaluation

NASA's Traffic Aware Planner (TAP) is a cockpit decision support tool that has the potential to achieve significant fuel and time savings when it is embedded in the data-rich Next Generation Air Transportation System (NextGen) airspace. To address a key step towards the operational deployment of TAP and the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR), a system evaluation was conducted in a representative flight environment in November, 2013. Numerous challenges were overcome to achieve this goal, including the porting of the foundational Autonomous Operations Planner (AOP) software from its original simulation-based, avionics-embedded environment to an Electronic Flight Bag (EFB) platform. A flight-test aircraft was modified to host the EFB, the TAP application, an Automatic Dependent Surveillance Broadcast (ADS-B) processor, and a satellite broadband datalink. Nine Evaluation Pilots conducted 26 hours of TAP assessments using four route profiles in the complex eastern and north-eastern United States airspace. Extensive avionics and video data were collected, supplemented by comprehensive inflight and post-flight questionnaires. TAP was verified to function properly in the live avionics and ADS-B environment, characterized by recorded data dropouts, latency, and ADS-B message fluctuations. Twelve TAP-generated optimization requests were submitted to ATC, of which nine were approved, and all of which resulted in fuel and/or time savings. Analysis of subjective workload data indicated that pilot interaction with TAP during flight operations did not induce additional cognitive loading. Additionally, analyses of post-flight questionnaire data showed that the pilots perceived TAP to be useful, understandable, intuitive, and easy to use. All program objectives were met, and the next phase of TAP development and evaluations with partner airlines is in planning for 2015.

Maris, John M.↗
NASA NTRS2002

Partially Decentralized Control Architectures for Satellite Formations

In a partially decentralized control architecture, more than one but less than all nodes have supervisory capability. This paper describes an approach to choosing the number of supervisors in such au architecture, based on a reliability vs. cost trade. It also considers the implications of these results for the design of navigation systems for satellite formations that could be controlled with a partially decentralized architecture. Using an assumed cost model, analytic and simulation-based results indicate that it may be cheaper to achieve a given overall system reliability with a partially decentralized architecture containing only a few supervisors, than with either fully decentralized or purely centralized architectures. Nominally, the subset of supervisors may act as centralized estimation and control nodes for corresponding subsets of the remaining subordinate nodes, and act as decentralized estimation and control peers with respect to each other. However, in the context of partially decentralized satellite formation control, the absolute positions and velocities of each spacecraft are unique, so that correlations which make estimates using only local information suboptimal only occur through common biases and process noise. Covariance and monte-carlo analysis of a simplified system show that this lack of correlation may allow simplification of the local estimators while preserving the global optimality of the maneuvers commanded by the supervisors.

Carpenter, J. Russell↗
NASA NTRS2023

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗
NASA NTRS2023

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗