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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 19 records

The Principle of Maximum Conformality Correctly Resolves the Renormalization-Scheme-Dependence Problem

In this paper, we clarify a serious misinterpretation and consequent misuse of the Principle of Maximum Conformality (PMC), which also can serve as a mini-review of PMC. In a recently published article, P. M. Stevenson has claimed that “the PMC is ineffective and does nothing to resolve the renormalization-scheme-dependence problem”, concluding incorrectly that the success of PMC predictions is due to the PMC being a “laborious, ad hoc, and back-door” version of the Principle of Minimal Sensitivity (PMS). We show that such conclusions are incorrect, deriving from a misinterpretation of the PMC and an overestimation of the applicability of the PMS. The purpose of the PMC is to achieve precise fixed-order pQCD predictions, free from conventional renormalization schemes and scale ambiguities. We demonstrate that the PMC predictions satisfy all the self-consistency conditions of the renormalization group and standard renormalization-group invariance; the PMC predictions are thus independent of any initial choice of renormalization scheme and scale. The scheme independence of the PMC is also ensured by commensurate scale relations, which relate different observables to each other. Moreover, in the Abelian limit, the PMC dovetails into the well-known Gell-Mann–Low framework, a method universally revered for its precision in QED calculations. Due to the elimination of factorially divergent renormalon terms, the PMC series not only attains a convergence behavior far superior to that of its conventional counterparts but also deftly curtails any residual scale dependence caused by the unknown higher-order terms. This refined convergence, coupled with its robust suppression of residual uncertainties, furnishes a sound and reliable foundation for estimating the contributions from unknown higher-order terms. Anchored in the bedrock of standard renormalization-group invariance, the PMC simultaneously eradicates the factorial divergences and eliminates superfluous systematic errors, which inversely provides a good foundation for achieving high-precision pQCD predictions. Consequently, owing to its rigorous theoretical underpinnings, the PMC is eminently applicable to virtually all high-energy hadronic processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computing Sensitivities in Evolutionary Systems: A Real-time Reduced Order Modeling Strategy

We present a new methodology for computing sensitivities in evolutionary systems using a model-driven low-rank approximation. To this end, we formulate a variational principle that seeks to minimize the distance between the time derivative of the reduced approximation and sensitivity dynamics. The first order optimality condition of the variational principle leads to a system of closed form evolution equations for an orthonormal basis and corresponding sensitivity coefficients. This approach allows for the computation of sensitivities with respect to a large number of parameters in an accurate and tractable manner by extracting correlations between different sensitivities on the fly. The presented method requires solving forward evolution equations, sidestepping the restrictions imposed by the forward/backward workflow of adjoint sensitivities. For example, the presented method, unlike the adjoint equation, does not impose any input/output load and can be used in applications in which real-time sensitivities are of interest. We demonstrate the utility of the method for three test cases: (1) computing sensitivity with respect to model parameters in the Rössler system, (2) computing sensitivity with respect to an infinite-dimensional forcing parameter in the chaotic Kuramoto--Sivashinsky equation, and (3) computing sensitivity with respect to reaction parameters for species transport in a turbulent reacting flow.

Reduced order model↗

Device and Container for Reheating and Sterilization

Long-duration space missions require the development of improved foods and novel packages that do not represent a significant disposal issue. In addition, it would also be desirable if rapid heating technologies could be used on Earth as well, to improve food quality during a sterilization process. For this purpose, a package equipped with electrodes was developed that will enable rapid reheating of contents via ohmic heating to serving temperature during space vehicle transit. Further, the package is designed with a resealing feature, which enables the package, once used, to contain and sterilize waste, including human waste for storage prior to jettison during a long-duration mission. Ohmic heating is a technology that has been investigated on and off for over a century. Literature indicates that foods processed by ohmic heating are of superior quality to their conventionally processed counterparts. This is due to the speed and uniformity of ohmic heating, which minimizes exposure of sensitive materials to high temperatures. In principle, the material may be heated rapidly to sterilization conditions, cooled rapidly, and stored. The ohmic heating device herein is incorporated within a package. While this by itself is not novel, a reusable feature also was developed with the intent that waste may be stored and re-sterilized within the packages. These would then serve a useful function after their use in food processing and storage. The enclosure should be designed to minimize mass (and for NASA's purposes, Equivalent System Mass, or ESM), while enabling the sterilization function. It should also be electrically insulating. For this reason, Ultem high-strength, machinable electrical insulator was used.

Sastry, Sudhir K.↗

Bid-in Price-Sensitive Load: A Comparison with Fixed Load in a Realistic Test System

Bulk power systems operations, in both simulation and practice, are often built on the principle of minimizing production costs, which assumes to first order that demand is fixed and that the only degrees of freedom for balancing generation and load are supply-side unit commitment and dispatch decisions. The purpose of this report is to interrogate the value of welfare-maximizing markets that not only physically balance demand and supply but also ensure that market outcomes provide consumer value by directly maximizing welfare, defined as the value of consumption minus production costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Superconducting quasiparticle-amplifying transmon: A qubit-based sensor for meV-scale phonons and single terahertz photons

With great interest from the quantum computing community, an immense amount of R&D effort has been invested into improving superconducting qubits. The technologies developed for the design and fabrication of these qubits can be directly applied to applications for ultralow-threshold particle detectors, e.g., low-mass dark matter and far-infrared photon sensing. We propose a novel energy-resolving sensor based on the transmon qubit architecture combined with a signal-enhancing superconducting quasiparticle amplification stage. We refer to these sensors as SQUATs: superconducting quasiparticle-amplifying transmons. We detail the operating principle and design of this new sensor and predict that, with minimal R&D effort, solid-state-based detectors patterned with these sensors can achieve sensitivity to single terahertz photons, and sensitivity to 1 meV phonons in the detector absorber substrate on the microsecond timescale. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗

Fluidic hydrogen detector production prototype development

A hydrogen gas sensor that can replace catalytic combustion sensors used to detect leaks in the liquid hydrogen transfer systems at Kennedy Space Center was developed. A fluidic sensor concept, based on the principle that the frequency of a fluidic oscillator is proportional to the square root of the molecular weight of its operating fluid, was utilized. To minimize sensitivity to pressure and temperature fluctuations, and to make the sensor specific for hydrogen, two oscillators are used. One oscillator operates on sample gas containing hydrogen, while the other operates on sample gas with the hydrogen converted to steam. The conversion is accomplished with a small catalytic converter. The frequency difference is taken, and the hydrogen concentration computed with a simple digital processing circuit. The output from the sensor is an analog signal proportional to hydrogen content. The sensor is shown to be accurate and insensitive to severe environmental disturbances. It is also specific for hydrogen, even with large helium concentrations in the sample gas.

Roe, G. W.↗

A Microseismometer for Terrestrial and Extraterrestrial Applications

The scientific and technical requirements of extraterrestrial seismology place severe demands on instrumentation. Performance in terms of sensitivity, stability, and frequency band must match that of the best terrestrial instruments, at a fraction of the size, mass, and power. In addition, this performance must be realized without operator intervention in harsh temperature, shock, and radiation environments. These constraints have forced us to examine some fundamental limits of accelerometer design in order to produce a small, rugged, sensitive seismometer. Silicon micromachined sensor technology offers techniques for the fabrication of monolithic, robust, compact, low-power and -mass accelerometers. However, currently available sensors offer inadequate sensitivity and bandwidth. Our implementation of an advanced silicon micro machined seismometer is based on principles developed at JPL for high-sensitivity position sensor technology. The use of silicon micro machining technology with these new principles should enable the fabrication of a 10(exp -11) g sensitivity seismometer with a bandwidth of at least 0.01 to 20 Hz. The low Q properties of pure single-crystal silicon are essential in order to minimize the Brownian thermal noise limitations generally characteristic of seismometers with small proof masses. A seismometer consists of a spring-supported proof mass and a transducer for measuring its motion. For long period motion a position sensor is generally used, for which the displacement is proportional to the ground acceleration. The mechanical sensitivity can be increased either by increasing the proof mass or decreasing the spring stiffness, neither of which is desirable for planetary applications. Our approach has been to use an ultra sensitive capacitive position sensor with a sensitivity of better than 10(exp -13) m/Hz(exp 1/2). This allows the use of a stiffer suspension and a smaller proof mass. We have built several prototypes using these principles, and tests show that these devices can exhibit performance comparable to state-of-the-art instruments.

Banerdt, W.↗

Application of quadratic optimization to supersonic inlet control

The application of linear stochastic optimal control theory to the design of the control system for the air intake (inlet) of a supersonic air-breathing propulsion system is discussed. The controls must maintain a stable inlet shock position in the presence of random airflow disturbances and prevent inlet unstart. Two different linear time invariant control systems are developed. One is designed to minimize a nonquadratic index, the expected frequency of inlet unstart, and the other is designed to minimize the mean square value of inlet shock motion. The quadratic equivalence principle is used to obtain the best linear controller that minimizes the nonquadratic performance index. The two systems are compared on the basis of unstart prevention, control effort requirements, and sensitivity to parameter variations.

Lehtinen, B.↗

Doping-induced spin reorientation in kagome magnet TmMn 6 ⁢Sn 6

The kagome-lattice compounds RMn 6 Sn 6 (R is a rare-earth element), where the Mn atoms form a kagome net in the basal plane, are currently attracting a great deal of attention as they have been shown to host complex magnetic textures and electronic topological states strongly sensitive to the choice of the R atom. Among the magnetic R atoms, TmMn 6 Sn 6 orders with the easy-plane magnetization forming a complex magnetic spiral along the c axis. Previous neutron studies carried out on polycrystalline samples found that Ga doping changes the magnetic anisotropy from easy-plane to easy-axis. Here, in this study, we present magnetic and magnetotransport measurements on a single crystal and first-principles calculations in the doping series of TmMn 6 Sn 6-x Ga x . We find that the magnetic properties are highly sensitive even to a small concentration of Ga. With minimal Ga substitution, the easy-plane anisotropy is maintained, which gradually changes to the easy-axis anisotropy with increasing Ga. We discuss these observations with respect to the effect of Ga doping on magnetocrystalline anisotropy and Tm crystal field.

Gazzah, Mohamed El [University of Notre Dame, IN (↗

Two-dimensional finite-element temperature variance analysis

The finite element method is extended to thermal analysis by forming a variance analysis of temperature results so that the sensitivity of predicted temperatures to uncertainties in input variables is determined. The temperature fields within a finite number of elements are described in terms of the temperatures of vertices and the variational principle is used to minimize the integral equation describing thermal potential energy. A computer calculation yields the desired solution matrix of predicted temperatures and provides information about initial thermal parameters and their associated errors. Sample calculations show that all predicted temperatures are most effected by temperature values along fixed boundaries; more accurate specifications of these temperatures reduce errors in thermal calculations.

Heuser, J. S.↗

Quantum machine learning with differential privacy

Abstract Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. There exists the potential for a quantum advantage due to the intractability of quantum operations on a classical computer. Many datasets used in machine learning are crowd sourced or contain some private information, but to the best of our knowledge, no current QML models are equipped with privacy-preserving features. This raises concerns as it is paramount that models do not expose sensitive information. Thus, privacy-preserving algorithms need to be implemented with QML. One solution is to make the machine learning algorithm differentially private, meaning the effect of a single data point on the training dataset is minimized. Differentially private machine learning models have been investigated, but differential privacy has not been thoroughly studied in the context of QML. In this study, we develop a hybrid quantum-classical model that is trained to preserve privacy using differentially private optimization algorithm. This marks the first proof-of-principle demonstration of privacy-preserving QML. The experiments demonstrate that differentially private QML can protect user-sensitive information without signficiantly diminishing model accuracy. Although the quantum model is simulated and tested on a classical computer, it demonstrates potential to be efficiently implemented on near-term quantum devices [noisy intermediate-scale quantum (NISQ)]. The approach’s success is illustrated via the classification of spatially classed two-dimensional datasets and a binary MNIST classification. This implementation of privacy-preserving QML will ensure confidentiality and accurate learning on NISQ technology.

97 MATHEMATICS AND COMPUTING↗

Thermokinetic mixing compounding for polymer composites – a comprehensive review

High-speed thermokinetic mixers (K-mixers) represent an advanced compounding technology that employs intense shear and friction to convert kinetic energy directly into thermal energy. This mechanism enables rapid mixing cycles, often under one minute, facilitating exceptional filler dispersion while minimizing the material’s thermal history. This is particularly effective for compounding challenging materials, including heat-sensitive biopolymers, wet filler feedstocks, and nanofillers prone to agglomeration. As the first comprehensive review of this technology, this article synthesizes the fundamental principles of thermokinetic mixing (K-mixing) and surveys recent advances in polymer composite fabrication. We contrast the working principles of K-mixers with conventional twin-screw extrusion, highlighting distinct advantages in dispersing nanoscale fillers, exfoliating layered materials, and processing wet cellulosic feedstocks and ultra-high filler loadings (e.g., 85 wt%). Furthermore, strategies to optimize filler–matrix interfacial bonding under rapid-processing constraints, such as the kinetic selection of compatibilizers and fiber surface treatments, are evaluated. Finally, we analyze key structure-processing-property relationships and outline future directions in scaling up, reactive processing, and hybrid material development.

Zhang, Xuefeng [University of Maine]↗

In Liquid Infrared Scattering Scanning Near-Field Optical Microscopy for Chemical and Biological Nanoimaging

Imaging biological systems with simultaneous intrinsic chemical specificity and nanometer spatial resolution in their typical native liquid environment has remained a long-standing challenge. In this paper we demonstrate a general approach of chemical nanoimaging in liquid based on infrared scattering scanning near-field optical microscopy (IR $s$-SNOM). It is enabled by combining AFM operation in a fluid cell with evanescent IR illumination via total internal reflection, which provides spatially confined excitation for minimized IR water absorption, reduced far-field background, and enhanced directional signal emission and sensitivity. We demonstrate in-liquid IR $s$-SNOM vibrational nanoimaging and conformational identification of catalase nano-crystals and spatio-spectral analysis of biomimetic peptoid sheets with monolayer sensitivity and chemical specificity at the few zeptomole level. This work establishes the principles of in-liquid and in-situ IR $s$-SNOM spectroscopic chemical nano-imaging and its general applicability to biomolecular, cellular, catalytic, electrochemical, or other interfaces and nano-systems in liquids or solutions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Label-free DNA biosensing by topological light confinement

Large-area and transparent all-dielectric metasurfaces sustaining photonic bound states in the continuum (BICs) provide a set of fundamental advantages for ultrasensitive biosensing. BICs bridge the gap of large effective mode volume with large experimental quality factor. Relying on the transduction mechanism of reactive sensing principle, herein, we first numerically study the potential of subwavelength confinement driven by topological decoupling from free space radiation for BIC-based biosensing. Then, we experimentally combine this capability with minimal and low-cost optical setup, applying the devised quasi-BIC resonator for PNA/DNA selective biosensing with real-time monitoring of the binding event. A sensitivity of 20 molecules per micron squared is achieved, i.e. ≃0.01 pg. Further enhancement can easily be envisaged, pointing out the possibility of single-molecule regime. This work aims at a precise and ultrasensitive approach for developing low-cost point-of-care tools suitable for routine disease prescreening analyses in laboratory, also adaptable to industrial production control.

59 BASIC BIOLOGICAL SCIENCES↗

The Demonstration of a Light Extinction Tomography System at the NASA Glenn Research Center's Icing Research Tunnel

A prototype light extinction tomography system has been developed for acquiring real-time in-situ icing cloud uniformity and density measurements in the NASA Glenn Research Center's Icing Research Tunnel (IRT). These measurements are currently obtained through periodic manual calibrations of the IRT. These calibrations are time consuming and assume that cloud uniformity and density does not greatly vary between the periodic calibrations. It is envisioned that the new light extinction tomography system will provide the means to make these measurements in-situ in real-time and minimize the need for these manual calibrations. This new system uses the principle of light extinction tomography to measure the spray density and distribution in the test section. The prototype system was installed and successfully demonstrated in the Icing Research Tunnel in early 2018. Data sets were acquired for several standard spray and simulated fault conditions to assess system capability and sensitivity. This paper will describe the prototype light extinction system, the theory behind it, and the results of the demonstration test that was conducted in the IRT.

Test Facility↗

The Demonstration of a Light Extinction Tomography System at the NASA Glenn Research Center's Icing Research Tunnel

A prototype light extinction tomography system has been developed for acquiring real-time in-situ icing cloud uniformity and density measurements in the NASA Glenn Research Center's Icing Research Tunnel (IRT). These measurements are currently obtained through periodic manual calibrations of the IRT. These calibrations are time consuming and assume that cloud uniformity and density does not greatly vary between the periodic calibrations. It is envisioned that the new light extinction tomography system will provide the means to make these measurements in-situ in real-time and minimize the need for these manual calibrations. This new system uses the principle of light extinction tomography to measure the spray density and distribution in the test section. The prototype system was installed and successfully demonstrated in the Icing Research Tunnel in early 2018. Data sets were acquired for several standard spray and simulated fault conditions to assess system capability and sensitivity. This paper will describe the prototype light extinction system, the theory behind it, and the results of the demonstration test that was conducted in the IRT.

Tomography↗

5-year lifetime hybrid superfluid helium dewar for the AXAF X-Ray Spectrometer (XRS)

The focal plane of the AXAF X-Ray Spectrometer requires an operating temperature of 0.1 K with a mission lifetime of 5 yrs. This demanding task is accomplished with a hybrid cryogenic subsystem consisting of mechanical coolers, a superfluid helium dewar and an adiabatic demagnetization refrigerator. By using mechanical coolers to remove heat from the dewar outer vapor-cooled shield, a 5-yr lifetime is achievable with only a 483-liter tank. This approach takes advantage of flight-proven, high-performance dewar technology and recent success in the development of split, Stirling-cycle mechanical coolers. Although the dewar design principles are similar to those used previously, parasitic heat flow is reduced to a new level by an optimized tension strap support system and careful attention to insulation system details. The benefit of the mechanical coolers is maximized by dewar interface design features that minimize parasitic heating and thermal impedance of the coupling. The dewar design and thermal performance analysis are discussed. Helium lifetime sensitivities and the effects of mechanical cooler failures are predicted.

Nieczkoski, Stephen J.↗

Energy Use in Quantum Data Centers: Scaling the Impact of Computer Architecture, Qubit Performance, Size, and Thermal Parameters

As quantum computers increase in size, the total energy used by a quantum data center, including the cooling, will become a greater concern. The cooling requirements of quantum computers, which operate at temperatures near absolute zero, are determined by computing system parameters, including the number and type of physical qubits, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. When combined with thermal system parameters such as cooling efficiency and cryostat heat transfer, the total energy use can be determined using a first-principles energy model. These models show that cooling of quantum computers differs in two fundamental ways from conventional data centers: (1) the energy required for cooling is much greater than the energy required for computation, and (2) the cooling loads are sensitive to the computational architecture. The temperature requirements for different qubit types can change energy requirements by orders of magnitude. Power use and computational power, as quantified by quantum volume, are analytically correlated. Approaches are identified for minimizing energy use in integrated quantum systems relative to computational power. Furthermore, designing a sustainable quantum computer will require both efficient cooling and system design that minimizes cooling requirements.

97 MATHEMATICS AND COMPUTING↗