Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Optimal experimental design”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Design of 1500V/200kW 99.6% Efficiency Dual Active Bridge Converters Based on 1700V SiC Power MOSFET Module

High efficiency, high density and galvanically isolated power converters are attractive for medium voltage high power applications. This paper presents a 1.5kV/200kW bidirectional Dual Active Bridge (DAB) converter using a newly developed 1.7kV SiC MOSFET module. The intended application is megawatt scale solid state transformer (SST) and 1500V PV inverter application using modular architecture. One novel model to estimate the turn-off loss using snubber capacitors is proposed and experimentally verified. An optimized PCB-based busbar design is introduced to reduce the voltage overshoot across the SiC device, making the design suitable for 1.5kVdc applications. The mechanism of how the optimized PCB-based busbar can reduce the voltage overshoot is quantitatively interpreted and experimentally verified. The DAB converter achieved an efficiency of 98.85% at 200kW and a maximum of 99.53% at 60kW. The maximum efficiency for series-resonant mode is 99.6% at 85kW and 99.3% at 200kW. The power density is 26W/inch3 (1.6MW/m3) which is much higher than traditional industry products.

Xu, Wei↗
DOE OSTI2020

Optimal Power Hardware-in-the-Loop Interfacing: Applying Modern Control For Design and Verification of High-Accuracy Interfaces

Here, we develop a novel approach to designing power hardware-in-the-loop (PHIL) simulation interfaces that maximizes simulation bandwidth and accuracy by leveraging a modern control framework that explicitly considers objectives on accuracy and can automatically synthesize an optimal controller that meets these objectives while stabilizing the closed-loop system. The method developed improves upon common approaches to PHIL interface design that typically involve multiple design steps for manual compensation and stabilization design that can result in interfaces that are stable but have suboptimal bandwidth and accuracy. The approach developed is general and can be applied to most PHIL system configurations. The modeling framework allows for the inclusion of scaling factors and hardware-under-test current injection models that are common to practical PHIL simulations and have significant impacts on stability. We also present practical methods and metrics for verifying the absolute accuracy of PHIL simulation results without relying on relative comparisons to potentially inaccurate models or previous simulation results. We demonstrate the accuracy evaluation method and show the improved performance achievable when using the optimal PHIL interface design approach in an experimental case study involving a 100-kVA battery inverter.

42 ENGINEERING↗
NASA NTRS1984

Grid flexibility and patching techniques

The numerical determination of combustor flowfields is of great value to the combustor designer. An a priori knowledge of the flow behavior can speed the combustor design process and reduce the number of experimental test rigs required to arrive at an optimal design. Even 2-D steady incompressible isothermal flow predictions are of use; many codes of this kind are available, each employing different techniques to surmount the difficulties arising from the nonlinearity of the governing equations and from typically irregular combustor geometries. Mapping techniques (algebraic and elliptic PDE), and adaptive grid methods (both multi-grid and grid embedding) as applied to axisymmetric combustors are discussed.

Keith, T. G.↗
NASA NTRS1974

Computer-aided space shuttle orbiter wing design study

An analytical and experimental investigation has been made to provide a space shuttle orbiter wing design that met the guideline requirements of landing performance, stability, and hypersonic trim for a specified center-of-gravity envelope. The analytical study was facilitated by the use of the Optimal Design Integration system (ODIN) and the experimental part of the investigation was conducted in the Langley low-turbulence pressure tunnel and the Langley continuous-flow hypersonic tunnel.

Phillips, W. P.↗
NASA NTRSDate not supplied

Clearance Sensitivity Mitigation in Small Core Compressors

As future aircraft become lighter and more aerodynamically efficient, thrust requirements will decrease, reducing the core size of the engine. Furthermore, in the pursuit of improved fuel burn, engine overall pressure ratio and bypass ratio will increase, further driving down engine core size. These drivers together mean that the core size, or corrected mass flow rate at the compressor exit, for future single-aisle aircraft applications will shrink below 3.0 lbm/s. Traditionally, this small core compressor size is in the domain of axi-centrifugal designs, machines that are typically less efficient and limited to pressure ratios of ~25 due to stress and thermomechanical fatigue in the centrifugal impeller. In this light, NASA, Pratt & Whitney and the Raytheon Technologies Research Center embarked upon a program to develop technologies to enable an all-axial high-pressure compressor with a core size below 3.0 lbm/s and an overall pressure ratio greater than 50. One of the challenges with an all-axial high-pressure compressor at this core size is the small span at the rear of the compressor. As core size is scaled down, the rotor tip clearances do not scale with span, leading to significant efficiency penalties. This paper documents a numerical and experimental effort to mitigate this penalty through design optimization and technology insertion, enabling an estimated 5 to 10% fuel burn reduction relative to 2020 best-in-class. The experimental program consisted of two builds of a high-speed rig: a baseline build and a second build to insert technology to manage large rotor tip gap/span ratios. The results demonstrated a reduction in the sensitivity of the compressor to large clearance ratios, which would be likely at the end-of-life of a small core application. The test campaign demonstrated that, with the insertion of technology, small core compressors can maintain a similar efficiency to current best-in-class large core size compressors. In addition to advancing the state-of-the-art of technology, the program also advanced the modeling standards for multistage compressors with large clearance-to-span ratios. The validation of this approach is described in the paper.

Axial Compressors↗
NASA NTRSDate not supplied

Clearance Sensitivity Mitigation in Small Core Compressors

As future aircraft become lighter and more aerodynamically efficient, thrust requirements will decrease, reducing the core size of the engine. Furthermore, in the pursuit of improved fuel burn, engine overall pressure ratio and bypass ratio will increase, further driving down engine core size. These drivers together mean that the core size, or corrected mass flow rate at the compressor exit, for future single-aisle aircraft applications will shrink below 3.0 lb/s. Traditionally, this small core compressor size is in the domain of axi-centrifugal designs, machines that are typically less efficient and limited to pressure ratios of ~25 due to stress and thermomechanical fatigue in the centrifugal impeller. In this light, NASA, Pratt & Whitney and the Raytheon Technologies Research Center embarked upon a program to develop technologies to enable an all-axial high-pressure compressor with a core size below 3.0 lb/s and an overall pressure ratio greater than 50. One of the challenges with an all-axial high-pressure compressor at this core size is the small span at the rear of the compressor. As core size is scaled down, the rotor tip clearances do not scale with span, leading to significant efficiency penalties. This paper documents a numerical and experimental effort to mitigate this penalty through design optimization and technology insertion, enabling an estimated 5 to 10% fuel burn reduction relative to 2020 best-in-class. The experimental program consisted of two builds of a high-speed rig: a baseline build and a second build to insert technology to manage large rotor tip gap/span ratios. The results demonstrated a reduction in the sensitivity of the compressor to large clearance ratios, which would be likely at the end-of-life of a small core application. The test campaign demonstrated that, with the insertion of technology, small core compressors can maintain a similar efficiency to current best-in-class large core size compressors. In addition to advancing the state-of-the-art of technology, the program also advanced the modeling standards for multistage compressors with large clearance-to-span ratios. The validation of this approach is described in the paper.

Axial Compressors↗
NASA NTRSDate not supplied

An Initial Assessment of Variable Depth Liner Optimization for Ducted Proprotor Applications

The rise of the Urban Air Mobility market has spurred the design of a new generation of novel aircraft. To aid industry and researchers interested in these types of aircraft, the Revolutionary Vertical Lift Technology project at NASA has developed a fleet of reference vehicles for system studies. A new six-passenger reference vehicle has recently been added to the research portfolio that has ducted proprotors for propulsors. The ducts present an opportunity to apply acoustic treatment to the interior of the duct that could target both tonal and broadband noise, representative of the sound produced by this type of propulsor. In this paper, design methodologies are presented to design a variable depth liner for this application. An optimizer is used to design multiple liners with variable chamber depths. Experimental results from normal impedance testing are compared to numerical predictions using the optimizer model and a finite element model. Results show that an optimizer can be used to design an acoustic liner with favorable performance for a broad range of frequencies, which could be appropriate for a ducted proprotor application.

Matthew B Galles↗
NASA NTRS1993

Reliability-based structural optimization: A proposed analytical-experimental study

An analytical and experimental study for assessing the potential of reliability-based structural optimization is proposed and described. In the study, competing designs obtained by deterministic and reliability-based optimization are compared. The experimental portion of the study is practical because the structure selected is a modular, actively and passively controlled truss that consists of many identical members, and because the competing designs are compared in terms of their dynamic performance and are not destroyed if failure occurs. The analytical portion of this study is illustrated on a 10-bar truss example. In the illustrative example, it is shown that reliability-based optimization can yield a design that is superior to an alternative design obtained by deterministic optimization. These analytical results provide motivation for the proposed study, which is underway.

Stroud, W. Jefferson↗
NASA NTRS1984

Research pressure instrumentation for NASA Space Shuttle main engine, modification no. 5

The objective of the research project described is to define and demonstrate methods to advance the state of the art of pressure sensors for the space shuttle main engine (SSME). Silicon piezoresistive technology was utilized in completing tasks: generation and testing of three transducer design concepts for solid state applications; silicon resistor characterization at cryogenic temperatures; experimental chip mounting characterization; frequency response optimization and prototype design and fabrication. Excellent silicon sensor performance was demonstrated at liquid nitrogen temperature. A silicon resistor ion implant dose was customized for SSME temperature requirements. A basic acoustic modeling software program was developed as a design tool to evaluate frequency response characteristics.

Anderson, P. J.↗
DOE OSTI2022

Transfer learning driven design optimization for inertial confinement fusion

Transfer learning is a promising approach to create predictive models that incorporate simulation and experimental data into a common framework. In this technique, a neural network is first trained on a large database of simulations and then partially retrained on sparse sets of experimental data to adjust predictions to be more consistent with reality. Previously, this technique has been used to create predictive models of Omega [Humbird et al., IEEE Trans. Plasma Sci. 48, 61–70 (2019)] and NIF [Humbird et al., Phys. Plasmas 28, 042709 (2021); Kustowski et al., Mach. Learn. 3, 015035 (2022)] inertial confinement fusion (ICF) experiments that are more accurate than simulations alone. Here, in this work, we conduct a transfer learning driven hypothetical ICF campaign in which the goal is to maximize experimental neutron yield via Bayesian optimization. The transfer learning model achieves yields within 5% of the maximum achievable yield in a modest-sized design space in fewer than 20 experiments. Furthermore, we demonstrate that this method is more efficient at optimizing designs than traditional model calibration techniques commonly employed in ICF design. Such an approach to ICF design could enable robust optimization of experimental performance under uncertainty.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2002

Structural Optimization of a Force Balance Using a Computational Experiment Design

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Parker, P. A.↗
NASA NTRSDate not supplied

Overview and Introduction of the Rotor Optimization for the Advancement of Mars eXploration (ROAMX) Project

Research in pursuit of rotorcraft flight on Mars has been ongoing since the late 1990s at NASA Ames Research Center. Since then, many other organizations have also begun researching rotary-wing flight on Mars. In 2014, the project that led to the first helicopter to fly on Mars began at the Jet Propulsion Laboratory. Ingenuity was developed as a joint effort between JPL, NASA Ames, NASA Langley, and AeroVironment. The Ingenuity Mars Helicopter made history in April 2021 as the first vehicle demonstrating controlled, powered flight on another planet and, in doing so, it has opened a new era of planetary aviation. Future, more capable Mars rotorcraft will be able to fly even further and carry significant science payload. At NASA Ames, through NASA Space Technology Mission Directorate funding, the research necessary to help develop the next generation of Mars rotorcraft has begun with the Rotor Optimization for the Advancement of Mars eXploration (ROAMX) project. The ROAMX project involves computationally and experimentally investigating aerodynamically efficient, compressible, low-Reynolds number airfoils for rotor blades and, further, new high-performance rotor designs. ROAMX is also developing and validating a rotor design methodology to optimize blades given specific mission requirements. The primary experimental effort of the ROAMX project is focused on rotor hover performance, but subsequent airfoil and rotor design advances are anticipated to carry over into improvements in forward flight efficiency. ROAMX is a collaboration between NASA Ames, JPL, the University of Maryland, AeroVironment, and Tohoku University.

Rotor Optimization for the Advancement of Mars eXp↗
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 OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Interleukin-2 superkines by computational design

Significance While computational engineering of therapeutic proteins is a desirable goal, in practice the optimization of protein–protein interactions requires substantial experimental intervention. We present here a computational approach that focuses on stabilizing core protein structures rather than engineering the protein–protein interface. Using this approach, we designed thermostabilized interleukin-2 (IL-2) variants that bind tightly to their receptor without experimental optimization, mimicking the properties of the yeast-display engineered IL-2 variant “super-2.” Our results suggest that structure-guided stabilization may be a general method for in silico affinity maturation of protein–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Uncertain characterization of reservoir fluids due to brittleness of equation of state regression

Equations of state (EoS) play a central role in modeling the phase equilibrium of fluid mixtures. Their parameterization involves fitting a model to experimental data, i.e., solving a nonlinear, non-convex, multivariate optimization problem. The latter requires one to select design variables, domains of definition for each variable, and weights assigned to individual measurements. We demonstrate that subjective choices of an optimization algorithm and an initial guess also impact the regression process. Consequently, EoS predictions are fundamentally uncertain even after the EoS tuning to a limited set of experimental data points. We demonstrate this observation for two hydrocarbon reservoir fluids, in which five properties of the heaviest carbon fraction are treated as design variables. While all the optimization algorithms and initial guesses match experimental data for the gas and liquid properties, the resulting EoS parameterizations lead to dramatically different predictions of the fluid’s thermophysical behavior in the unsampled pressure and temperature regions. In conclusion, we propose the probabilistic treatment of design variables to quantify the predictive uncertainty of the resulting fluid models.

15 GEOTHERMAL ENERGY↗
NASA NTRS2001

Quick Cooling and Filling Through a Single Port for Cryogenic Transfer Operations

Improved technology for the efficient transfer of cryogens is needed for future on-orbit fueling and remote Lunar/Mars operations. The cooling and filling of a liquid nitrogen (LN2) test vessel through a single port were investigated in a series of experiments. A new 'in-space' transfer tube design concept was used to demonstrate the ability to quickly cool and load cryogens through a single feed-through connection. Three different fill tube configurations with three different diameters were tested. The tubes providing the quickest cooldown time and the quickest fill time for the test article tank were determined. The results demonstrated a clear trade-off between cooling time and filling time for the optimum tube design. This experimental study is intended to improve technology for future flight tank designs by reducing fill system size, complexity, heat leak rate, and operations time. These results may be applied to Space Shuttle Power Reactant Storage and Distribution (PRSD) System upgrades and other future applications. Further study and experimental analysis for optimization of the fill tube design are in progress.

Jones, J. R.↗
DOE OSTI2021

Statistical Multiobjective Optimization of Thiospinel CoNi 2 S 4 Nanocrystal Synthesis via Design of Experiments

Thiospinels, such as CoNi 2 S 4 , are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi 2 S 4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi 2 S 4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 2 5–2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/$\bar{d}$) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Furthermore, our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗