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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 181 records · Page 10

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization (MDAO) tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Lung, Shun-fat↗

Potential benefits and optimization of cool-coated office buildings: A case study in Chongqing, China

Increasing envelope facet albedos considerably reduces solar heat gain, thus yielding building cooling energy savings. Few studies have explored the potential benefits of utilizing cool coatings on building envelopes (“cool-coated buildings”) based on life-cycle cost analysis. A holistic approach integrating the field testing, building energy simulation, and a 20-year life-cycle-based optimization was developed to explore cool-coated building performance and the maximum net savings of optimal building envelope retrofit and design. Experimental results showed that applying cool coatings to a west wall of an office building in Chongqing, China reduced its exterior surface temperature by up to 9.3 °C in summer. Additionally, simulation results showed that in Chongqing, making the roof and walls cool could reduce annual HVAC electricity use by up to 11.9% in old buildings (with poorly insulated envelopes) and up to 5.9% in new buildings. Retrofitting old buildings with a cool roof provided the net savings per modified area with present values up to 42.8 CNY/m2; retrofitting a new building with a cool roof or cool walls was not cost-effective. Optimizing both envelope insulation and envelope albedo can achieve 5.6 times the net savings of optimizing the insulation only, and 1.6 times that of optimizing albedo only.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Utilization of the CW magnetrons as coherent RF sources for superconducting RF accelerators

CW magnetrons designed and optimized for industrial heaters, driven by an injection-locking signal, were suggested to power Superconducting RF (SRF) cavities. However, the CW magnetrons, which are regenerative generators, are intended to operate in self-excitation mode, so, for reliable starting they use a large regenerative gain, causing a large regenerative instability in operation. Thus, power supply ripple, even shot noise, etc., lead to multiple sidebands forming a quasi-continuous noise spectrum at the carrier frequency. Therefore, in the traditionally used mode of operation and control, such magnetrons are inapplicable for powering high Q-factor SRF cavities. A new approach to operation and control of CW magnetrons considering non-stationary processes during start-up and operation makes it possible to find a mode of almost coherent RF generation of tubes with a significant reduction in regenerative instability and noise and increased efficiency. In our work is presented substantiation for the newly developed mode with an analysis of the new approach based on experimental results. •In this article, for the first time, non-stationary, regenerative processes are considered during the start-up and operation of CW magnetrons for powering high-Q superconducting RF cavities.•An analytical study, confirmed by experiments, showed that the traditionally used modes of starting and operating CW magnetrons are not suitable for powering high-Q superconducting RF cavities.•In fact, to make CW magnetrons suitable for such cavities, the physics of starting and operating CW magnetrons must be changed. This has been demonstrated in our work.•In developing the Stimulated Coherent Generation Mode [NIM A 980 (2020) 164366], we have shown the suitability of this mode for starting and operating CW magnetrons for high-Q superconducting RF cavities.•Analytical analysis, verified experimentally, substantiates in our article the suitability of the “Mode of stimulated coherent generation” of CW magnetrons for powering high-Q superconducting cavities in pulsed and continuous modes.

43 PARTICLE ACCELERATORS↗

Bayesian optimization algorithms for accelerator physics

Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design and model calibration in simulations. The effectiveness of optimization algorithms in discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. The accelerator physics community has recognized the advantages of Bayesian optimization algorithms, which leverage statistical surrogate models of objective functions to effectively address complex optimization challenges, especially in the presence of noise during accelerator operation and in resource-intensive physics simulations. In this review article, we offer a conceptual overview of applying Bayesian optimization techniques toward solving optimization problems in accelerator physics. We begin by providing a straightforward explanation of the essential components that make up Bayesian optimization techniques. We then give an overview of current and previous work applying and modifying these techniques to solve accelerator physics challenges. Finally, we explore practical implementation strategies for Bayesian optimization algorithms to maximize their performance, enabling users to effectively address complex optimization challenges in real-time beam control and accelerator design. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study

The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.

Johannsen, G.↗

Space transportation vehicle design evaluation using saturated designs

An important objective in the preliminary design and evaluation of space transportation vehicles is to find the best values of design variables that optimize the performance characteristic (e.g. dry weight). For a given configuration, the vehicle performance can be determined by the use of complex sizing and performance evaluation computer programs. These complex computer programs utilize iterative algorithms and they are generally too expensive and/or difficult to use directly in multidisciplinary design optimization. An alternative is to use response surface methodology (RSM) and obtain quadratic polynomial approximations to the functional relationships between performance characteristics and design variables. In RSM, these approximation models are then used to determine optimum design parameter values and for rapid sensitivity studies. Constructing a second-order model requires that 'n' design parameters be studied at least at 3 levels (values) so that the coefficients in the model can be estimated. There, 3(n) factorial experiments (point designs or observations) may be necessary. For small values of 'n' such as two or three, this design works well. However, when a large number of design parameters are under study, the number of design points required for a full-factorial design may become excessive. Fortunately, these quadratic polynomial approximations can be obtained by selecting an efficient design matrix using central composite designs (CCD) from design of experiments theory. Each unique point design from the CCD matrix is then conducted using computerized analysis tools (e.g. POST, CONSIZ, etc.). In the next step, least squares regression analysis is used to calculate the quadratic polynomial coefficients from the data. However, in some multidisciplinary applications involving a large number of design variables and several disciplines, the computerized performance synthesis programs may get too time consuming and expensive to run even with the use of efficient central composite designs. In such cases, it may be preferable to keep the number of design points to an absolute minimum and trade some model accuracy with cost. For this purpose, another class of experimental designs, called saturated D-optimal designs may be utilized for generating a matrix of vehicle designs. A design is called saturated when the number of design points is exactly equal to the number of terms in the model to be fitted. As a result, saturated designs require the absolute minimum number of design points ((n+1)(n+2)/s) to estimate the quadratic polynomial model coefficients. Saturated designs can be generated using the D-optimality criterion. A good saturated design should give rise to least squares estimates with minimum generalized variance.

Unal, Resit↗

Optimization of the Second Target Station cold source moderators using an automated workflow

The Second Target Station (STS) at the US Department of Energy’s Oak Ridge National Laboratory is designed to become the world’s highest peak-brightness spallation source of cold neutrons. Successful completion of the STS, which is currently in the preliminary design phase, will provide transformative new capabilities to examine novel materials for future technologies. At STS, neutrons will be generated by spallation reactions in a solid tungsten target. They will be moderated and thermalized in two cold (20 K) para-hydrogen moderators. Careful optimization of these moderators is essential to the project’s success. To find optimal moderator designs, an advanced optimization workflow integrates high-fidelity neutronics calculations using the Monte Carlo N-Particle (MCNP) transport code MCNP6.2 with state-of-the-art optimization algorithms in the Dakota optimization toolkit. For each design iteration, a parametrized solid CAD geometry is generated in Creo and automatically converted into an unstructured mesh geometry by Attila 4MC for the neutronics calculation with MCNP. Iterations repeat until optimal designs are found. Herein this paper presents the results of a sensitivity and optimization study for the cylindrical and tube moderators. Both moderators can be optimized for maximum peak brightness, maximum time-integrated brightness, or any combination between these extremes. Maximum peak brightness is achieved by using smaller optimal dimensions of the moderators, whereas maximum time-integrated brightness is achieved by using larger dimensions. A Pareto front details the designs that optimally balance both brightness metrics. The Pareto front can be found in only 40–110 iterations with 4–5 design parameters when using the efficient global and Pareto-set optimization algorithms in Dakota. Additionally, important engineering constraints can be taken into account, such as the coupling between the cylindrical moderator radius and aluminum vessel wall thicknesses required to ensure structural integrity of the vessels. This interaction has a significant impact on the resulting optimal designs. Our new, highly efficient, fully automated optimization workflow will be used to optimize additional STS components in the future and can be adopted for design and optimization studies at other experimental neutron and accelerator facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimal binning of correlated measurements

Experimental measurements are commonly represented on a discrete grid, requiring a balance between granularity and statistical noise. Two strategies have traditionally been used to improve such representations: selecting an appropriate bin width to control discretization error and applying kernel-based smoothing to suppress fluctuations. Despite their shared goal, these approaches have largely developed independently, without a unified statistical description of how discretization and correlation jointly determine measurement precision. Here, we extend the discussion of optimal interval averaging to a correlation-aware setting by Gaussian process regression, which explicitly accounts for correlations among neighboring bins. Starting from first principles, we derive the mean-squared error of discretized measurements and obtain closed-form asymptotic expressions for the optimal bin width and correlation length. When recast in reduced variables, the theory reveals distinct universal scaling laws governing the error in the correlation-free and correlation-controlled regimes. Characterized by intrinsically smooth intensity profiles and counting-based statistics, neutron scattering measurements are well suited for demonstrating the enhanced error contraction enabled by inter-bin correlations. We show that such improvement is achievable over the experimentally accessible Q-range and across multiple instruments and material systems. These results show that explicitly accounting for correlations systematically reshapes the limits of precision in discretized, noise-limited measurements. More broadly, the framework provides a transferable statistical foundation for optimizing data representation, inference, and experimental design across the physical and data sciences.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

Development of a self-lubricating high-efficiency hybrid seal composed of carbon nanotube-coated metal meshes for CSP turbomachinery (SETO CPS #36333 Final Report)

In turbomachinery, internal leakage flow accounts for up to 3% of the total thermodynamic cycle energy loss. Tradeoff must be made between the sealing efficiency (smaller clearance) and the friction and wear issues for interfering with the shaft (larger clearance). This ORNL-Danfoss joint effort developed a novel hybrid seal composed of carbon nanotube (CNT)-coated metal meshes. The CNT growth process was based on a self-catalyzing chemical vapor deposition and these multiwall CNTs were well aligned with high crystallinity. This hybrid material structure takes advantage of the CNT’s low-friction nature and uses the metal mesh as an extendable backbone. Full-scale experimental seals were designed, fabricated, and optimized for sealing performance and durability. The CNT-coated metal mesh seal demonstrated superior gas sealing efficiency to the baseline labyrinth seal and significantly improved shaft surface protection compared with the state-of-the-art superalloy brush seal on the static rig and full-scale compressor dynamometer tests. The CNT-metal mesh seal is low-cost and scalable and can potentially benefit wide applications, including CSP and other power generation, marine, automotive, and HVAC.

36 MATERIALS SCIENCE↗

Hepatocellular Metabolic Profile: Understanding Post-Thawing Metabolic Shift in Primary Hepatocytes In Vitro

Primary human hepatocytes (PHHs) are widely used as in vitro models for liver function and drug metabolism studies, yet their metabolic stability post-thawing remains an open question. To better characterize early metabolic changes, we conducted a time-course experiment using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze metabolic shifts in PHHs cultured in suspension. Unexposed and exposed (acetaminophen-treated) samples were evaluated, and TITAN analysis was applied to determine the time point of maximal metabolic change at both individual metabolite and global metabolic profile levels. Our results indicate that the majority of metabolic shifts occur within the first five hours post-thawing. In the early culture time points, substantial metabolic overlap was observed between unexposed and exposed cells, suggesting a conserved biological response likely related to cellular recovery. However, at later time points, metabolite profiles diverged, with acetaminophen treatment-specific metabolic changes emerging, potentially reflecting differences in homeostatic restoration versus hepatotoxic responses. Our study highlights the importance of considering early post-thawing metabolic dynamics in experimental design and offers insights for optimizing hepatocyte culture protocols to better replicate in vivo physiological conditions.

59 BASIC BIOLOGICAL SCIENCES↗

gpCAM v8

gpCAM is a Python software for large-scale Gaussian-Process driven uncertainty quantification, Bayesian Optimization, and Autonomous Experimentation. It is designed with maximum flexibility and customizability while offering record-breaking computing capabilities. In 2023 gpCAM broke the world record for Gaussian processes on large datasets set in 2019. Through clever programming and math, Gaussian Process building blocks, such as prior mean, kernel, and noise functions maintain their mathematical flexibility while supporting acceleration and scaling. This flexibility means that the approximation and uncertainty quantification can be domain-aware and extended over exotic input and output spaces.

Noack, Marcus↗

Overview of two-dimensional airfoil research at Ames Research Center

The five basic elements of the two dimensional airfoil research program at Ames Research Center are illustrated. These elements are experimental, theoretical (including computational), validation, design optimization, and industry interaction. Each area is briefly discussed.

Chapman, G. T.↗

Application of numerical optimization to the design of advanced supercritical airfoils

An application of numerical optimization to the design of advanced airfoils for transonic aircraft showed that low-drag sections can be developed for a given design Mach number without an accompanying drag increase at lower Mach numbers. This is achieved by imposing a constraint on the drag coefficient at an off-design Mach number while minimizing the drag coefficient at the design Mach number. This multiple design-point numerical optimization has been implemented with the use of airfoil shape functions which permit a wide range of attainable profiles during the optimization process. Analytical data for the starting airfoil shape, a single design-point optimized shape, and a double design-point optimized shape are presented. Experimental data obtained in the NASA Ames two-by two-foot wind tunnel are also presented and discussed.

Johnson, R. R.↗

Recent Progress on the VASIMR

Experimental and theoretical studies on the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) have continued through a NASA led collaborative program involving several research groups. In the experimental area, performance characterization of the VASIMR helicon plasma source has been obtained over a portion of the parameter space, with helium and hydrogen propellant. Density (10(exp 18) - 10(exp 19)/ cubic meter) and temperature (5 eV) were measured at moderate degree of ionization in two separate experimental devices. Helicon design improvement and optimization will be discussed. Experiments with the ion cyclotron resonance heating (ICRH) subsection have begun and preliminary results will be discussed. Theoretical picture and integrated numerical simulation continue to be refined to account for the main physics elements of the VASIMR, including RF absorption and particle acceleration with subsequent detachment in the magnetic nozzle.

ChangDiaz, Franklin R.↗

Research in Support of the Use of Rankine Cycle Energy Conversion Systems for Space Power and Propulsion

This is the report of a Scientific Working Group (SWG) formed by NASA to determine the feasibility of using a liquid metal cooled nuclear reactor and Rankine energy conversion cycle for dual purpose power and propulsion in space. This is a high level technical report which is intended for use by NASA management in program planning. The SWG was composed of a team of specialists in nuclear energy and multiphase flow and heat transfer technology from academia, national laboratories, NASA and industry. The SWG has identified the key technology issues that need to be addressed and have recommended an integrated short term (approx. 2 years) and a long term (approx. 10 year) research and development (R&D) program to qualify a Rankine cycle power plant for use in space. This research is ultimately intended to give NASA and its contractors the ability to reliably predict both steady and transient multiphase flow and heat transfer phenomena at reduced gravity, so they can analyze and optimize designs and scale-up experimental data on Rankine cycle components and systems. In addition, some of these results should also be useful for the analysis and design of various multiphase life support and thermal management systems being considered by NASA.

Lahey, Richard T., Jr.↗

TPSAS-NF1676L-14336-DND

Problem Statement: Develop robust CFD-based methods for rapid design and analysis of supersonic cruise aircraft that are highly efficient, and have a low sonic boom. What is our approach? - Advanced Efficient Analysis / Design Methods - Develop computational algorithms and techniques for rapid high fidelity analysis of supersonic fluid flow phenomena, which will also contribute to multi-fidelity analysis / design tools. - Experimental Validation - Validate concepts for design optimization of both high aerodynamic efficiency and low sonic boom.

Linda Bangert↗

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↗

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↗