Results for “Advanced Optimization” — Page 76

NASA NTRS1985

Wheel configurations for combined energy storage and attitude control systems

Integrated power and attitude control system (IPACS) studies performed over a decade ago established the feasibility of simultaneously storing electrical energy in wheels and utilizing the resulting momentum for spacecraft attitude control. It was shown that such a system possessed many advantages over other contemporary energy storage and attitude control systems in many applications. More recent technology advances in composite rotors, magnetic bearings, and power control electronics have triggered new optimism regarding the feasibility and merits of such a system. This paper presents the results of a recent study whose focus was to define an advanced IPACS and to evaluate its merits for the Space Station application. Emphasis is given to the selection of the wheel configuration to perform the combined functions. A component design concept is developed to establish the system performance capability. A system-level trade study, including life-cycle costing, is performed to define the merits of the system relative to two other candidate systems. It is concluded that an advanced IPACS concept is not only feasible but offers substantial savings in mass and life-cycle cost.

Oglevie, R. E.↗

NASA NTRS1983

The development of a generalized advanced propeller analysis system

A Generalized Advanced Propeller Analysis System (GAPAS) is being developed to provide both an optimized design and a performance evaluation capability. The technology areas incorporated in GAPAS include propeller aerodynamic performance, airfoil loading, acoustics, structural analysis and aeroelasticity. The propeller analyses include the most advanced, fully-developed technologies in a modular but unified system. The program will treat multi-bladed propellers having straight or swept blades operating on aircraft at speeds to Mach 0.8 and altitudes to 40,000 feet. The purpose of this paper is twofold. First, it will introduce the GAPAS program to the general industry; and second, since the GAPAS program will be made available for general applications, it is also intended to be a status report on the development stage of the program.

Glatt, L.↗

DOE OSTI2019

Performance of asynchronous optimized Schwarz with one-sided communication

In asynchronous iterative methods on distributed-memory computers, processes update their local solutions using data from other processes without an implicit or explicit global synchronization that corresponds to advancing the global iteration counter. Here in this work, we test the asynchronous optimized Schwarz domain-decomposition iterative method using various one-sided (remote direct memory access) communication schemes with passive target completion. The results show that when one-sided communication is well-supported, the asynchronous version of optimized Schwarz can outperform the synchronous version even for perfectly balanced partitionings of the problem on a supercomputer with uniform nodes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1979

Composite structural materials

A multifaceted program is described in which aeronautical, mechanical, and materials engineers interact to develop composite aircraft structures. Topics covered include: (1) the design of an advanced composite elevator and a proposed spar and rib assembly; (2) optimizing fiber orientation in the vicinity of heavily loaded joints; (3) failure mechanisms and delamination; (4) the construction of an ultralight sailplane; (5) computer-aided design; finite element analysis programs, preprocessor development, and array preprocessor for SPAR; (6) advanced analysis methods for composite structures; (7) ultrasonic nondestructive testing; (8) physical properties of epoxy resins and composites; (9) fatigue in composite materials, and (10) transverse thermal expansion of carbon/epoxy composites.

Ansell, G. S.↗

DOE OSTI2017

Final Project Report for DOE/EERE High-Capacity and Low-Cost Hydrogen-Storage Sorbents for Automotive Applications

This report provides a review of the objectives, progress, and milestones of the research conducted during this project on the topic of developing innovative metal-organic frameworks (MOFs) and porous organic polymers (POPs) for high-capacity and low-cost hydrogen-storage sorbents in automotive applications.1 The objectives of the proposed research were to develop new materials as next-generation hydrogen storage sorbents that meet or exceed DOE’s 2017 performance targets of gravimetric capacity of 0.055 kg H 2 /kg system and volumetric capacity of 0.040 kg H 2 /L system at a cost of $400/kg H 2 stored . Texas A&M University (TAMU) and Argonne National Laboratory (ANL) collaborated in developing low-cost and high-capacity hydrogen-storage sorbents with appropriate stability, sorption kinetics, and thermal conductivity. The research scope and methods developed to achieve the project’s goals include the following: Advanced ligand design and synthesis to construct MOF sorbents with optimal hydrogen storage capacities, low cost and high stability; Substantially improve the hydrogen uptake capacity and chemical stability of MOF-based sorbents by incorporating high valent metal ions during synthesis or through the post-synthetic metal metathesis oxidation approach; Enhance sorbent storage capacity through material engineering and characterization; Generate a better understanding of the H 2 -sorbent interaction through advanced characterization and simulation. Over the course of the project 5 different MOFs were developed and studied: PCN-250, PCN-12, PCN-12’, PCN-608 and PCN-609.2-3 Two different samples were submitted to the National Renewable Energy Laboratory (NREL) in order to validate their hydrogen adsorption capacity, PCN-250 and PCN-12. Neither of these samples reached the project’s Go/No-Go requirements but the data obtained did further prove the hypothesis that the presence of open metal sites oriented towards MOF pores help to surpass the predicted hydrogen uptakes described by Chahine’s rule.4 These observations are believed to have a major impact on the hydrogen storage community, and may potentially lead to the development of a material that could meet the DOE goals for hydrogen storage systems for automotive applications.

08 HYDROGEN↗

NASA NTRSDate not supplied

A Nonlinear Schur Complement Solver for CFD-Based Multidisciplinary Models

CFD-based multidisciplinary models are the fundamental building blocks of multidis- ciplinary design optimization frameworks. Linear and nonlinear solutions of these coupled models are difficult, especially when the Jacobian matrices represent a saddle point problem, where a block-diagonal corresponding to a discipline is non-invertible. These scenarios necessitate the use of a coupled solver algorithm such as the Newton’s method instead of the popular block Gauss– Seidel-based methods because of this non-invertible block. To address this challenge, we introduce a nonlinear Schur complement solver suitable for CFD-based multidisciplinary models. The solver leverages the specialized linear and nonlinear solvers of the CFD code, and therefore, does not require the solution of a large coupled linear system as the coupled Newton’s method. Further- more, because the solver primarily uses the specialized linear and nonlinear solvers of the CFD code, it does not suffer from the same robustness limitations as the coupled Newton’s method. In this work, we will implement this solver in NASA’s OpenMDAO framework and demonstrate its effectiveness using a CFD-based aeropropulsive model. The solver will contribute to the develop- ment of aeropropulsive design optimization and CFD-based design optimization methods with the ultimate goal of accelerating the design and integration of advanced propulsion systems.

Nonlinear Solvers↗

DOE OSTI2025

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗

NASA NTRS2016

Swift follow-up of gravitational wave triggers: results from the first aLIGO run and optimization for the future

During its first observing run, in late 2015, the advanced Laser Interferometer Gravitational-wave Observatory facility announced three gravitational wave (GW) triggers to electromagnetic follow-up partners. Two of these have since been confirmed as being of astrophysical origin: both are binary black hole mergers at ∼500 Mpc; the other trigger was later found not to be astrophysical. In this paper, we report on the Swift follow-up observations of the second and third triggers, including details of 21 X-ray sources detected; none of which can be associated with the GW event. We also consider the challenges that the next GW observing run will bring as the sensitivity and hence typical distance of GW events will increase. We discuss how to effectively use galaxy catalogues to prioritize areas for follow-up, especially in the presence of distance estimates from the GW data. We also consider two galaxy catalogues and suggest that the high completeness at larger distances of the 2MASS Photometric Redshift catalogue makes it very well suited to optimize Swift follow-up observations.

P. A. Evans↗

NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management, FPM, AOP, UAM, deconflicti↗

NASA NTRSDate not supplied

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management↗

DOE OSTI2018

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies, software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Droplet microfluidics for synthetic biology

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer-Based Hydrogen Production Facility: Preprint

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at the National Renewable Energy Laboratory (NREL)'s Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

DOE OSTI2015

WE-EF-BRA-07: High Performance Preclinical Irradiation Through Optimized Dual Focal Spot Dose Painting and Online Virtual Isocenter Radiation Field Targeting

Purpose: Advances in radiotherapy practice facilitated by collimation systems to shape radiation fields and image guidance to target these conformal beams have motivated proposals for more complex dose patterns to improve the therapeutic ratio. Recent progress in small animal radiotherapy platforms has provided the foundation to validate the efficacy of such interventions, but robustly delivering heterogeneous dose distributions at the scale and accuracy demanded by preclinical studies remains challenging. This work proposes a dual focal spot optimization method to paint spatially heterogeneous dose regions and an online virtual isocenter targeting method to accurately target the dose distributions. Methods: Two-dimensional dose kernels were empirically measured for the 1 mm diameter circular collimator with radiochromic film in a solid water phantom for the small and large x-ray focal spots on the X-RAD 225Cx microirradiator. These kernels were used in an optimization framework which determined a set of animal stage positions, beam-on times, and focal spot settings to optimally deliver a given desired dose distribution. An online method was developed which defined a virtual treatment isocenter based on a single image projection of the collimated radiation field. The method was demonstrated by optimization of a 6 mm circular 2 Gy target adjoining a 4 mm semicircular avoidance region. Results: The dual focal spot technique improved the optimized dose distribution with the proportion of avoidance region receiving more than 0.5 Gy reduced by 40% compared to the large focal spot technique. Targeting tests performed by irradiating ball bearing targets on radiochromic film pieced revealed the online targeting method improved the three-dimensional accuracy from 0.48 mm to 0.15 mm. Conclusion: The dual focal spot optimization and online virtual isocenter targeting framework is a robust option for delivering dose at the preclinical level and provides a new experimental option for unique radiobiological investigations This work is supported, in part, by the Natural Sciences and Engineering Research Council of Canada and a Mitacs-Accelerate fellowship. P.E. Lindsay, and D.A. Jaffray are listed as inventors of the system described herein. This system has been licensed to Precision X-Ray Inc. for commercial development.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2006

In-Space Radiator Shape Optimization using Genetic Algorithms

Future space exploration missions will require the development of more advanced in-space radiators. These radiators should be highly efficient and lightweight, deployable heat rejection systems. Typical radiators for in-space heat mitigation commonly comprise a substantial portion of the total vehicle mass. A small mass savings of even 5-10% can greatly improve vehicle performance. The objective of this paper is to present the development of detailed tools for the analysis and design of in-space radiators using evolutionary computation techniques. The optimality criterion is defined as a two-dimensional radiator with a shape demonstrating the smallest mass for the greatest overall heat transfer, thus the end result is a set of highly functional radiator designs. This cross-disciplinary work combines topology optimization and thermal analysis design by means of a genetic algorithm The proposed design tool consists of the following steps; design parameterization based on the exterior boundary of the radiator, objective function definition (mass minimization and heat loss maximization), objective function evaluation via finite element analysis (thermal radiation analysis) and optimization based on evolutionary algorithms. The radiator design problem is defined as follows: the input force is a driving temperature and the output reaction is heat loss. Appropriate modeling of the space environment is added to capture its effect on the radiator. The design parameters chosen for this radiator shape optimization problem fall into two classes, variable height along the width of the radiator and a spline curve defining the -material boundary of the radiator. The implementation of multiple design parameter schemes allows the user to have more confidence in the radiator optimization tool upon demonstration of convergence between the two design parameter schemes. This tool easily allows the user to manipulate the driving temperature regions thus permitting detailed design of in-space radiators for unique situations. Preliminary results indicate an optimized shape following that of the temperature distribution regions in the "cooler" portions of the radiator. The results closely follow the expected radiator shape.

Hull, Patrick V.↗

DOE OSTI2015

MO-FG-207-00: Technological Advances in PET/MR Imaging

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-01: Technological Advances and Challenges: Experience with the First Integrated Whole-Body PET/MRI

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-02: Technological Advances and Challenges: Experience with Time-Of-Flight PET Combined with 3-Tesla MRI

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗