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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Spacecraft boost and abort guidance and control systems requirement study, boost dynamics and control analysis study. Exhibit A: Boost dynamics and control anlaysis

The simulation developments for use in dynamics and control analysis during boost from liftoff to orbit insertion are reported. Also included are wind response studies of the NR-GD 161B/B9T delta wing booster/delta wing orbiter configuration, the MSC 036B/280 inch solid rocket motor configuration, the MSC 040A/L0X-propane liquid injection TVC configuration, the MSC 040C/dual solid rocket motor configuration, and the MSC 049/solid rocket motor configuration. All of the latest math models (rigid and flexible body) developed for the MSC/GD Space Shuttle Functional Simulator, are included.

Williams, F. E.↗
NASA NTRS1982

Computer simulations of optimum boost and buck-boost converters

The development of mathematicl models suitable for minimum weight boost and buck-boost converter designs are presented. The facility of an augumented Lagrangian (ALAG) multiplier-based nonlinear programming technique is demonstrated for minimum weight design optimizations of boost and buck-boost power converters. ALAG-based computer simulation results for those two minimum weight designs are discussed. Certain important features of ALAG are presented in the framework of a comprehensive design example for boost and buck-boost power converter design optimization. The study provides refreshing design insight of power converters and presents such information as weight annd loss profiles of various semiconductor components and magnetics as a function of the switching frequency.

Rahman, S.↗
NASA NTRS1981

Nonlinear program based optimization of boost and buck-boost converter designs

The facility of an Augmented Lagrangian (ALAG) multiplier based nonlinear programming technique is demonstrated for minimum-weight design optimizations of boost and buck-boost power converters. Certain important features of ALAG are presented in the framework of a comprehensive design example for buck-boost power converter design optimization. The study provides refreshing design insight of power converters and presents such information as weight and loss profiles of various semiconductor components and magnetics as a function of the switching frequency.

Rahman, S.↗
DOE OSTI2024

Waning immunity and IgG4 responses following bivalent mRNA boosting

Messenger RNA (mRNA) vaccines were highly effective against the ancestral SARS-CoV-2 strain, but the efficacy of bivalent mRNA boosters against XBB variants was substantially lower. Here, we show limited durability of neutralizing antibody (NAb) responses against XBB variants and isotype switching to immunoglobulin G4 (IgG4) responses following bivalent mRNA boosting. Bivalent mRNA boosting elicited modest XBB.1-, XBB.1.5-, and XBB.1.16-specific NAbs that waned rapidly within 3 months. In contrast, bivalent mRNA boosting induced more robust and sustained NAbs against the ancestral WA1/2020 strain, suggesting immune imprinting. Following bivalent mRNA boosting, serum antibody responses were primarily IgG2 and IgG4 responses with poor Fc functional activity. In contrast, a third monovalent mRNA immunization boosted all isotypes including IgG1 and IgG3 with robust Fc functional activity. These data show substantial immune imprinting for the ancestral spike and isotype switching to IgG4 responses following bivalent mRNA boosting, with important implications for future booster designs and boosting strategies.

Science & Technology - Other Topics↗
DOE OSTI2024

PAIReD jet: A multi-pronged resonance tagging strategy across all Lorentz boosts

We propose a new approach of jet-based event reconstruction that aims to optimally exploit correlations between the products of a hadronic multi-pronged decay across all Lorentz boost regimes. The new approach utilizes clustered small-radius jets as seeds to define unconventional jets, referred to as PAIReD jets. The constituents of these jets are subsequently used as inputs to machine learning-based algorithms to identify the flavor content of the jet. We demonstrate that this approach achieves higher efficiencies in the reconstruction of signal events containing heavy-flavor jets compared to other event reconstruction strategies at all Lorentz boost regimes. Classifiers trained on PAIReD jets also have significantly better background rejections compared to those based on traditional event reconstruction approaches using small-radius jets at low Lorentz boost regimes. The combined effect of a higher signal reconstruction efficiency and better classification performance results in a two to four times stronger rejection of light-flavor jets compared to conventional strategies at low Lorentz-boosts, and rejection rates similar to classifiers based on large-radius multi-pronged jets at high Lorentz-boost regimes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2005

Series-Connected Buck Boost Regulators

A series-connected buck boost regulator (SCBBR) is an electronic circuit that bucks a power-supply voltage to a lower regulated value or boosts it to a higher regulated value. The concept of the SCBBR is a generalization of the concept of the SCBR, which was reported in "Series-Connected Boost Regulators" (LEW-15918), NASA Tech Briefs, Vol. 23, No. 7 (July 1997), page 42. Relative to prior DC-voltage-regulator concepts, the SCBBR concept can yield significant reductions in weight and increases in power-conversion efficiency in many applications in which input/output voltage ratios are relatively small and isolation is not required, as solar-array regulation or battery charging with DC-bus regulation. Usually, a DC voltage regulator is designed to include a DC-to-DC converter to reduce its power loss, size, and weight. Advances in components, increases in operating frequencies, and improved circuit topologies have led to continual increases in efficiency and/or decreases in the sizes and weights of DC voltage regulators. The primary source of inefficiency in the DC-to-DC converter portion of a voltage regulator is the conduction loss and, especially at high frequencies, the switching loss. Although improved components and topology can reduce the switching loss, the reduction is limited by the fact that the converter generally switches all the power being regulated. Like the SCBR concept, the SCBBR concept involves a circuit configuration in which only a fraction of the power is switched, so that the switching loss is reduced by an amount that is largely independent of the specific components and circuit topology used. In an SCBBR, the amount of power switched by the DC-to-DC converter is only the amount needed to make up the difference between the input and output bus voltage. The remaining majority of the power passes through the converter without being switched. The weight and power loss of a DC-to-DC converter are determined primarily by the amount of power processed. In the SCBBR, the unswitched majority of the power is passed through with very little power loss, and little if any increase in the sizes of the converter components is needed to enable the components to handle the unswitched power. As a result, the power-conversion efficiency of the regulator can be very high, as shown in the example of Figure 1. A basic SCBBR includes a DC-to-DC converter (see Figure 2). The switches and primary winding of a transformer in the converter is connected across the input bus, while the secondary winding and switches are connected in series with the output bus, so that the output voltage is the sum of the input voltage and the secondary voltage of the converter. In the breadboard SCBBR, the input voltage applied to the primary winding is switched by use of metal oxide/semiconductor field-effect transistors (MOSFETs) in a full bridge circuit; the secondary winding is center-tapped, with two MOSFET switches and diode rectifiers connected in opposed series in each leg. The sets of opposed switches and rectifiers are what enable operation in either a boost or a buck mode. In the boost mode, input voltage and current, and the output voltage and current are all positive; that is, the secondary voltage is added to the input voltage and the net output voltage can be regulated at a value equal or greater than the input voltage. In the buck mode, input voltage is still positive and the current still flows in the same direction in the secondary, but the switches are controlled such that some power flows from the secondary to the primary. The voltage across the secondary and the current into the primary are reversed. The result is that the output voltage is lower than the input voltage, and some power is recirculated from the converter secondary back to the input. Quantitatively, the advantage of an SCBBR is a direct function of the regulation range required. If, for example, a regulation range of 20 percent is required for a 500-W supply, th it suffices to design the DC-to-DC converter in the SCBBR for a power rating of only 100 W. The switching loss and size are much smaller than those of a conventional regulator that must be rated for switching of all 500 W. The reduction in size and the increase in efficiency are not directly proportional to switched-power ratio of 5:1 because the additional switches contribute some conduction loss and the input and output filters must be larger than those typically required for a 100-W converter. Nevertheless, the power loss and the size can be much smaller than those of a 500-W converter.

Birchenough, Arthur G.↗
DOE OSTI2024

Subsampling of Parametric Models with Bifidelity Boosting

Least squares regression is a ubiquitous tool for building emulators (a.k.a. surrogate models) of problems across science and engineering for purposes such as design space exploration and uncertainty quantification. When the regression data are generated using an experimental design process (e.g., a quadrature grid) involving computationally expensive models, or when the data size is large, sketching techniques have shown promise at reducing the cost of the construction of the regression model while ensuring accuracy comparable to that of the full data. However, random sketching strategies, such as those based on leverage scores, lead to regression errors that are random and may exhibit large variability. To mitigate this issue, we present a novel boosting approach that leverages cheaper, lower-fidelity data of the problem at hand to identify the best sketch among a set of candidate sketches. This in turn specifies the sketch of the intended high-fidelity model and the associated data. We provide theoretical analyses of this bifidelity boosting (BFB) approach and discuss the conditions the low- and high-fidelity data must satisfy for a successful boosting. In doing so, we derive a bound on the residual norm of the BFB sketched solution relating it to its ideal, but computationally expensive, high-fidelity boosted counterpart. Finally, empirical results on both manufactured and PDE data corroborate the theoretical analyses and illustrate the efficacy of the BFB solution in reducing the regression error, as compared to the nonboosted solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Reconstruction of boosted and resolved multi-Higgs-boson events with symmetry-preserving attention networks

The production of multiple Higgs bosons at the CERN LHC provides a direct way to measure the trilinear and quartic Higgs self-interaction strengths as well as potential access to beyond the standard model effects that can enhance production at large transverse momentum p T . The largest event fraction arises from the fully hadronic final state in which every Higgs boson decays to a bottom quark-antiquark pair ($b\bar{b}$). This introduces a combinatorial challenge known as the jet assignment problem: assigning jets to sets representing Higgs boson candidates. Symmetry-preserving attention networks (SPA-Nets) have been developed to address this challenge. However, the complexity of jet assignment increases when simultaneously considering both H → $b\bar{b}$ reconstruction possibilities, i.e., two “resolved” small-radius jets each containing a shower initiated by a b quark or one “boosted” large-radius jet containing a merged shower initiated by a $b\bar{b}$ pair. The latter improves the reconstruction efficiency at high p T . In this work, we introduce a generalization to the SPA-Net approach to simultaneously consider both boosted and resolved reconstruction possibilities and unambiguously interpret an event as “fully resolved”, “fully boosted”, or in between. We report the performance of baseline methods, the original SPA-Net approach, and our generalized version on nonresonant HH and HHH production at the LHC. Considering both boosted and resolved topologies, our SPA-Net approach increases the Higgs boson reconstruction purity by 56–80% and the efficiency by 37–38% compared to the baseline method depending on the final state.

Higgs Production↗
DOE OSTI2025

Search for inelastic boosted dark matter with the ICARUS detector at the Gran Sasso Underground National Laboratory

We present the result of a search for inelastic boosted dark matter using the data corresponding to an exposure of 0.13 kton · year , collected by the ICARUS T-600 detector during its 2012–2013 operational period at the INFN Gran Sasso Underground National Laboratory. The benchmark boosted dark matter model features a multiparticle dark sector with a U ( 1 ) ′ gauge boson, the dark photon. The kinetic mixing of the dark photon with the Standard Model photon allows for a portal between the dark sector and the visible sector. The inelastic boosted dark matter interaction occurs when a dark matter particle inelastically scatters with an electron in the ICARUS detector, producing an outgoing, heavier dark sector state which subsequently decays back down to the dark matter particle, emitting a dark photon. The dark photon subsequently couples to a Standard Model photon through kinetic mixing. The Standard Model photon then converts to an electron-positron pair in the detector. This interaction process provides a distinct experimental signature that consists of a recoil electron from the primary interaction and an associated electron-positron pair from the secondary vertex. After analyzing 4,134 triggered events, the search results in zero observed events. Exclusion limits are set in the dark photon mass and coupling ( m X , ε ) parameter space for several selected optimal boosted dark matter mass sets and cover previously unexplored parameter space. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Addressing bias in bagging and boosting regression models

As artificial intelligence (AI) becomes widespread, there is increasing attention on investigating bias in machine learning (ML) models. Previous research concentrated on classification problems, with little emphasis on regression models. This paper presents an easy-to-apply and effective methodology for mitigating bias in bagging and boosting regression models, that is also applicable to any model trained through minimizing a differentiable loss function. Our methodology measures bias rigorously and extends the ML model's loss function with a regularization term to penalize high correlations between model errors and protected attributes. We applied our approach to three popular tree-based ensemble models: a random forest model (RF), a gradient-boosted model (GBT), and an extreme gradient boosting model (XGBoost). We implemented our methodology on a case study for predicting road-level traffic volume, where RF, GBT, and XGBoost models were shown to have high accuracy. Despite high accuracy, the ML models were shown to perform poorly on roads in minority-populated areas. Our bias mitigation approach reduced minority-related bias by over 50%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Comprehensive Efficiency Analysis of Seven-Switch Current-Source Inverter Based on Voltage-Boost Function and Genetic Algorithm

This paper investigates the voltage-boost features of the emerging seven-switch current-source inverter (H7-CSI) to improve the efficiency of the CSI-based motor drive system. The switching transient and power loss model of the H7-CSI topology during voltage-boost operation are analyzed in detail. The effects of the boost function on the switching and conduction loss of the H7-CSI topology are investigated. A genetic algorithm has been introduced that makes it possible to optimize the H7-CSI’s modulation index to minimize its power loss. Experimental results for the H7-CSI unit show that this optimization can reduce the power loss by 10.6%.

42 ENGINEERING↗
NASA NTRSDate not supplied

Differential Equation Approximation Using Gradient-Boosted Quantile Regression

The operation of cyber-physical-human (CPH) systems is subject to various epistemic and aleatory uncertainties. Overall trustworthiness of CPH systems relies on the trustworthiness of its components and their interactions. It is important that computational models comprising the cyber component of CPH provide predictions accompanied by a measure of confidence in model outcomes. Uncertainty quantification (UQ) and propagation are especially important in safety critical CPH systems. Gradient-boosted trees is a modeling approach capable both of learning the dynamics of a system and performing UQ. In this paper, we devise a method for using gradient boosting to learn the dynamics of a second order differential equation and estimate uncertainty at the same time. We do this by creating a custom loss function that trains the model to approximate the second derivative of a noisy time series, and to penalize based on a parameter that corresponds to the desired quantile. The resulting gradient boosting model can simulate stochastic trajectories of the system given a single starting point, that is, it can estimate both the expected trajectory and its uncertainty. We show that the uncertainty estimation is well calibrated and that the model can learn the dynamics even in the presence of noise. We demonstrate the approach on a simple cartpole system.

Autonomous systems↗
DOE OSTI2024

Generalized boost transformations in finite volumes and application to Hamiltonian methods

The investigation of hadron interactions within lattice QCD has been facilitated by the well-known quantisation condition, linking scattering phase shifts to finite-volume energies. Additionally, the ability to utilise systems at finite total boosts has been pivotal in smoothly charting the energy-dependent behaviour of these phase shifts. The existing implementations of the quantization condition at finite boosts rely on momentum transformations between rest and moving frames, defined directly in terms of the energy eigenvalues. This energy dependence is unsuitable in the formulation of a Hamiltonian. In this work, we introduce a novel approach to generalise the three-momentum boost prescription, enabling the incorporation of energy-independent finite-volume Hamiltonians within moving frames. We demonstrate the application of our method through numerical comparisons, employing a phenomenological ππ scattering example.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Cosmic-ray boosted inelastic dark matter from neutrino-emitting active galactic nuclei

Cosmic rays may scatter off dark matter particles in active galactic nuclei, where both the densities of cosmic rays and dark matter are expected to be very large. These scatterings could yield a flux of boosted dark matter particles directly detectable on Earth, which enhances the sensitivity of dark matter direct detection and neutrino experiments to light and inelastic dark matter models. Here we calculate the cosmic-ray boosted dark matter flux from the neutrino-emitting active galactic nuclei, NGC 1068 and TXS 0506+056, by considering realistic cosmic-ray distributions, deep inelastic scatterings, and mass splittings in the dark sector. From this we derive novel bounds from these sources on light and/or inelastic dark matter models with Super-K and XENONnT. We find that cosmic-ray boosted dark matter from neutrino-emitting active galactic nuclei can test regions of parameter space favored to reproduce the observed relic abundance of dark matter in the Universe, and that are otherwise experimentally inaccessible.

Gustafson, R. Andrew [Virginia Tech.; KEK, Tsukuba↗
DOE OSTI2025

Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at √(s) = 13 TeV

Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to bb̅ or cc̅, have been developed and deployed across a range of physics analyses. This paper highlights their performance on simulated events, and summarizes novel calibration techniques using proton-proton collision data collected at √(s) = 13 TeV during the 2016–2018 LHC data-taking period. Three dedicated methods are used for the calibration in multijet events, leveraging either machine learning techniques, the presence of muons within energetic boosted jets, or the reconstruction of hadronically decaying high-energy Z bosons. The calibration results, obtained through a combination of these approaches, are presented and discussed.

Pattern recognition↗