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Results for “Advanced 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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Improved Broadband Liner Optimization Applied to the Advanced Noise Control Fan

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more desirable. This paper describes improvements to a previously established broadband acoustic liner optimization process using the Advanced Noise Control Fan rig as a demonstrator. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom designs are carried through design, fabrication, and testing to validate the efficacy of the design process. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of these liner designs. This study also provides an application for demonstrating the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.

Nark, Douglas M.↗
NASA NTRS1992

Finite element method for optimal guidance of an advanced launch vehicle

A temporal finite element based on a mixed form of Hamilton's weak principle is summarized for optimal control problems. The resulting weak Hamiltonian finite element method is extended to allow for discontinuities in the states and/or discontinuities in the system equations. An extension of the formulation to allow for control inequality constraints is also presented. The formulation does not require element quadrature, and it produces a sparse system of nonlinear algebraic equations. To evaluate its feasibility for real-time guidance applications, this approach is applied to the trajectory optimization of a four-state, two-stage model with inequality constraints for an advanced launch vehicle. Numerical results for this model are presented and compared to results from a multiple-shooting code. The results show the accuracy and computational efficiency of the finite element method.

Hodges, Dewey H.↗
DOE OSTI2024

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗
DOE OSTI2026

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1989

A weak Hamiltonian finite element method for optimal guidance of an advanced launch vehicle

A temporal finite-element method based on a mixed form of the Hamiltonian weak principle is presented for optimal control problems. The mixed form of this principle contains both states and costates as primary variables, which are expanded in terms of nodal values and simple shape functions. Time derivatives of the states and costates do not appear in the governing variational equation; the only quantities whose time derivatives appear therein are virtual states and virtual costates. Numerical results are presented for an elementary trajectory optimization problem; they show very good agreement with the exact solution along with excellent computational efficiency and self-starting capability. The feasibility of this approach for real-time guidance applications is evaluated. A simplified model for an advanced launch vehicle application that is suitable for finite-element solution is presented.

Hodges, Dewey H.↗
NASA NTRS2004

A Web Centric Architecture for Deploying Multi-Disciplinary Engineering Design Processes

There are continuous needs for engineering organizations to improve their design process. Current state of the art techniques use computational simulations to predict design performance, and optimize it through advanced design methods. These tools have been used mostly by individual engineers. This paper presents an architecture for achieving results at an organization level beyond individual level. The next set of gains in process improvement will come from improving the effective use of computers and software within a whole organization, not just for an individual. The architecture takes advantage of state of the art capabilities to produce a Web based system to carry engineering design into the future. To illustrate deployment of the architecture, a case study for implementing advanced multidisciplinary design optimization processes such as Bi-Level Integrated System Synthesis is discussed. Another example for rolling-out a design process for Design for Six Sigma is also described. Each example explains how an organization can effectively infuse engineering practice with new design methods and retain the knowledge over time.

Woyak, Scott↗
NASA NTRS1993

Approximate optimal guidance for the advanced launch system

A real-time guidance scheme for the problem of maximizing the payload into orbit subject to the equations of motion for a rocket over a spherical, non-rotating earth is presented. An approximate optimal launch guidance law is developed based upon an asymptotic expansion of the Hamilton - Jacobi - Bellman or dynamic programming equation. The expansion is performed in terms of a small parameter, which is used to separate the dynamics of the problem into primary and perturbation dynamics. For the zeroth-order problem the small parameter is set to zero and a closed-form solution to the zeroth-order expansion term of Hamilton - Jacobi - Bellman equation is obtained. Higher-order terms of the expansion include the effects of the neglected perturbation dynamics. These higher-order terms are determined from the solution of first-order linear partial differential equations requiring only the evaluation of quadratures. This technique is preferred as a real-time, on-line guidance scheme to alternative numerical iterative optimization schemes because of the unreliable convergence properties of these iterative guidance schemes and because the quadratures needed for the approximate optimal guidance law can be performed rapidly and by parallel processing. Even if the approximate solution is not nearly optimal, when using this technique the zeroth-order solution always provides a path which satisfies the terminal constraints. Results for two-degree-of-freedom simulations are presented for the simplified problem of flight in the equatorial plane and compared to the guidance scheme generated by the shooting method which is an iterative second-order technique.

Feeley, T. S.↗
DOE OSTI2026

Automated ICRF heating surrogate modeling via machine learning

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗
NASA NTRS1990

An approach to optimal guidance of an advanced launch vehicle concept

An approximate solution for the maximum payload trajectory of a two-stage launch vehicle using a regular perturbation technique is presented. A zero-order solution for a two-stage vehicle based on a flat-earth approximation and negligible atmospheric effects is obtained in closed form. High-order correction terms are obtained from the solution of nonhomogeneous, first-order linear differential equations by quadrature. This promises the capability for an onboard optimal guidance law implementation.

Leung, Martin S.↗
DOE OSTI2024

Nonconvex Robust Optimization for the Design and Operation of Advanced Energy Systems Using PyROS

This work discusses recent advances of the two-stage robust optimization (RO) solver PyROS and applications to advanced energy systems optimization. To demonstrate the computational performance and reliability of PyROS, a study on a monoethanolamine (MEA)-based CO2 absorption flowsheet is presented. (Near-)robust feasible designs for CO2 absorption flowsheet at high carbon capture are obtained with the PyROS solver. The results demonstrate that the PyROS solver, including recent extensions to multi-stage RO settings, provides a reliable avenue to optimize the design and operation of advanced energy systems subject to various sources of parametric uncertainty.

Sherman, Jason↗
NASA NTRS1996

Optimal 3D Viewing with Adaptive Stereo Displays for Advanced Telemanipulation

A method of optimal 3D viewing based on adaptive displays of stereo images is presented for advanced telemanipulation. The method provides the viewer with the capability of accurately observing a virtual 3D object or local scene of his/her choice with minimum distortion.

3D viewing advanced telemanipulation telemanipulat↗
DOE OSTI2024

AEOLUS: Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems

The AEOLUS Center is dedicated to developing a unified optimization-under-uncertainty framework for (1) learning predictive models from data and (2) optimizing experiments, processes, and designs governed by these models, all driven by complex, uncertain energy systems. AEOLUS addressed the critical need for principled, rigorous, scalable, and structure-exploiting capabilities for exploring parameter and decision spaces of complex forward simulation models---the so-called outer loop. This report summarizes the work done under DE-SC0021077 on (1) nonlocal models for solidification problems, (2) a multifidelity method for a nonlocal diffusion model, and (3) multifidelity Monte Carlo methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems (Final Report for AEOLUS)

The AEOLUS Center is dedicated to developing a unified optimization-under-uncertainty framework for: (1) learning predictive models from data; and (2) optimizing experiments, processes, and designs governed by these models, all driven by complex, uncertain energy systems. AEOLUS addresses the critical need for principled, rigorous, scalable, and structure-exploiting capabilities for exploring parameter and decision spaces of complex forward simulation models. This report summarizes the key highlights of our research during the period of performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

Orbit Transfer Vehicle Engine Study. Phase A, extension 1: Advanced expander cycle engine optimization

The performance optimization of expander cycle engines at vacuum thrust levels of 10K, 15K, and 20K lb is discussed. The optimization is conducted for a maximum engine length with an extendible nozzle in the retracted position of 60 inches and an engine mixture ratio of 6.0:1. The thrust chamber geometry and cycle analyses are documented. In addition, the sensitivity of a recommended baseline expander cycle to component performance variations is determined and chilldown/start propellant consumptions are estimated.

Mellish, J. A.↗
NASA NTRS1991

Advanced air revitalization for optimized crew and plant environments

The Hybrid Air Revitalization System (HARS) closed ecosystem concept presented encompasses electrochemical CO2 and O2 separators, in conjunction with a mechanical condenser/separator for maintaining CO2, O2, and humidity levels in crew and plant habitats at optimal conditions. HARS requires no expendables, and allows flexible process control on the bases of electrochemical cell current, temperature, and airflow rate variations. HARS capacity can be easily increased through the incorporation of additional chemical cells. Detailed system flowcharts are provided.

Lee, M. G.↗
NASA NTRS1992

Recent advances in integrated multidisciplinary optimization of rotorcraft

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Adelman, Howard M.↗