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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 145 records · Page 8

Assessing the reliability of medical resource demand models in the context of COVID-19

Abstract Background Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain. Methods Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available athttps://doi.org/10.5281/zenodo.13712387. Results Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations. Conclusions The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.

Medical Informatics↗

Data from Genotype-Environment-Management Interactions in Biomass Yield and Feedstock Composition of Photoperiod-Sensitive Energy Sorghum

Recently introduced photoperiod-sensitive (PS) biomass sorghum ( Sorghum bicolor L. Moench) needs to be investigated for yield potential under different cultivation environments with reasonable nitrogen (N) inputs. The objectives of this study were to (1) evaluate the biomass yield and feedstock quality of four sorghum hybrids with different levels of PS ranging from very PS (VPS) hybrids and to moderate PS (MPS) hybrids, and (2) determine the optimal N inputs (0~168 kg N ha−1) under four environments: combinations of both temperate (Urbana, IL) and subtropical (College Station, TX) regions during 2018 and 2019. Compared to TX, the PS sorghums in central IL showed higher yield potential and steady feedstock production with an extended day length and with less precipitation variability, especially for the VPS hybrids. The mean dry matter (DM) yields of VPS hybrids were 20.5 Mg DM ha−1 and 17.7 Mg DM ha−1 in IL and TX, respectively. The highest N use efficiency occurred at a low N rate of 56 kg N ha−1 by improving approximately 33 kg DM ha−1 per 1.0 kg N ha−1 input. Approximately 70% of the PS sorghum biomass can be utilized for biofuel production, consisting of 58-65% of the cell-wall components and 4-11% of the soluble sugar. This study demonstrated that the rainfed temperate area (e.g., IL) has a great potential for the sustainable cultivation of PS energy sorghum due to their observed high yield potential, stable production, and low N requirements.

Biomass Analytics↗

Input-output characterization of an ultrasonic testing system by digital signal analysis

Ultrasonic test system input-output characteristics were investigated by directly coupling the transmitting and receiving transducers face to face without a test specimen. Some of the fundamentals of digital signal processing were summarized. Input and output signals were digitized by using a digital oscilloscope, and the digitized data were processed in a microcomputer by using digital signal-processing techniques. The continuous-time test system was modeled as a discrete-time, linear, shift-invariant system. In estimating the unit-sample response and frequency response of the discrete-time system, it was necessary to use digital filtering to remove low-amplitude noise, which interfered with deconvolution calculations. A digital bandpass filter constructed with the assistance of a Blackman window and a rectangular time window were used. Approximations of the impulse response and the frequency response of the continuous-time test system were obtained by linearly interpolating the defining points of the unit-sample response and the frequency response of the discrete-time system. The test system behaved as a linear-phase bandpass filter in the frequency range 0.6 to 2.3 MHz. These frequencies were selected in accordance with the criterion that they were 6 dB below the maximum peak of the amplitude of the frequency response. The output of the system to various inputs was predicted and the results were compared with the corresponding measurements on the system.

Williams, J. H., Jr.↗

Dynamic analysis of spur gears using computer program DANST

DANST is a computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the effect on dynamic load and tooth bending stress of spur gears due to operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratio ranging from one to three. It was designed to be easy to use, and it is extensively documented by comments in the source code. This report describes the installation and use of DANST. It covers input data requirements and presents examples. The report also compares DANST predictions for gear tooth loads and bending stress to experimental and finite element results.

Oswald, Fred B.↗

Dynamic analysis of spur gears using computer program DANST

DANST is a computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the effect on dynamic load and tooth bending stress of spur gears due to operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratio ranging from one to three. It was designed to be easy to use, and it is extensively documented by comments in the source code. This report describes the installation and use of DANST. It covers input data requirements and presents examples. The report also compares DANST predictions for gear tooth loads and bending stress to experimental and finite element results.

Oswald, Fred B.↗

Overview of nuclear fragementation models and needs

It has been known for some time that adequate assessment of spacecraft requirements and concomitant estimates of astronaut radiation exposures from galactic cosmic radiation requires accurate, quantitative methods for characterizing these radiation fields as they pass through thick absorbers. The main nuclear interaction processes involved are nuclear elastic an inelastic collisions, and nuclear breakup (fragmentation) and electromagnetic dissociation (EMD). Nuclear fragmenation and EMD are important because they alter the elemental and isotopic composition of the transported radiation fields. At present, there is no suitable accurate theory for predicting nuclear fragmentation cross sections for all collision pairs and energies of interest in space radiation protection. Typical cross-section differences between theory and experiment range from about 25 percent to a factor of two. The resulting errors in transported flux, for high linear energy transfer (LET) particles, are compared to these cross-sections errors. In this overview, theoretical models of heavy ion fragmentation currently used to generate input data bases for cosmic-ray transport and shielding codes are reviewed. Their shortcomings are discussed. Further actions needed to improve their accuracy and generality are presented.

Townsend, L. W.↗

Impact of AMS-02 Measurements on Reducing GCR Model Uncertainties

For vehicle design, shield optimization, mission planning, and astronaut risk assessment, the exposure from galactic cosmic rays (GCR) poses a significant and complex problem both in low Earth orbit and in deep space. To address this problem, various computational tools have been developed to quantify the exposure and risk in a wide range of scenarios. Generally, the tool used to describe the ambient GCR environment provides the input into subsequent computational tools and is therefore a critical component of end-to-end procedures. Over the past few years, several researchers have independently and very carefully compared some of the widely used GCR models to more rigorously characterize model differences and quantify uncertainties. All of the GCR models studied rely heavily on calibrating to available near-Earth measurements of GCR particle energy spectra, typically over restricted energy regions and short time periods. In this work, we first review recent sensitivity studies quantifying the ions and energies in the ambient GCR environment of greatest importance to exposure quantities behind shielding. Currently available measurements used to calibrate and validate GCR models are also summarized within this context. It is shown that the AMS-II measurements will fill a critically important gap in the measurement database. The emergence of AMS-II measurements also provides a unique opportunity to validate existing models against measurements that were not used to calibrate free parameters in the empirical descriptions. Discussion is given regarding rigorous approaches to implement the independent validation efforts, followed by recalibration of empirical parameters.

Slaba, T. C.↗

Applications of Parallel-Element, Embedded Mesh-Cap Acoustic Liner Concepts

This study explores progress achieved with 2DOF, 3DOF, and MDOF acoustic liners constructed with mesh caps embedded within a honeycomb core. These liner configurations offer potential for broadband noise reduction, and are suitable for conventional aircraft implementation. Samples for each configuration are tested in the NASA normal incidence tube and grazing flow impedance tube, with and without a wire mesh facesheet. Impedances based on these measured data compare favorably with those predicted using a transmission line impedance prediction model. Predicted impedances are then used as input for an aeroacoustic propagation code to compute axial acoustic pressure distributions in the grazing flow tube. These predicted distributions compare favorably with the corresponding measured distributions at frequencies away from the frequency of peak attenuation, but suffer slight degradation for frequencies very near the peak attenuation frequency, where the predicted results are sensitive to input impedance changes. As expected, the noise reduction frequency range increases as more degrees of freedom are included. Although the specific results achieved herein may differ from those that would be achieved with other 2DOF, 3DOF, and MDOF liners, this comparison highlights some of the key features that can be exploited in the design of parallel-element, embedded mesh-cap liners.

Jones, M. G.↗

Multimodal Data Fusion via Entropy Minimization

The use of gradient-based data-driven models to solve a range of real-world remote sensing problems can in practice be limited by the uniformity of available data. Use of data from disparate sensor types, resolutions, and qualities typically requires compromises based on assumptions that are made prior to model training and may not necessarily be optimal given over-arching objectives. For example, while deep neural networks (NNs) are state-of-the-art in a variety of target detection problems, training them typically requires either limiting the training data to a subset over which uniformity can be enforced or training independent models which subsequently require additional score fusion. The method we introduce here seeks to leverage the benefits of both approaches by allowing correlated inputs from different data sources to co-influence preferred model solutions, while maintaining flexibility over missing and mismatching data. In this work we propose a new data fusion technique for gradient updated models based on entropy minimization and experimentally validate it on a hyperspectral target detection dataset. We demonstrate superior performance compared to currently available techniques using a range of realistic data scenarios, where available data has limited spacial overlap and resolution.

97 MATHEMATICS AND COMPUTING↗

Techno-economic Analysis of the Cryogenic Flux Capacitor Compared to Other forms of Hydrogen Production and Storage

The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. The hydrogens storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 49% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at equivalent densities. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce GH2. The TEA compares pure hydrogen burning in a combined cycle gas turbine (CCGT) to hydrogen fuel cells with an overall net power output of 650 MW. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity is developed based on the capital cost and operating cost of the systems. Sensitivities are discussed around the cost of natural gas, ranging from 1.93 USD per MMBTU to 6.75 USD per MMBTU, and carbon dioxide disposal, ranging from 7 USD per tonne to 10 USD per tonne. For comparison to the conventional CCGT baseline, a baseload scenario is adopted with 85% capacity factor. The results of the study show that onsite hydrogen generation from SMR is about 1 to 3 USD per kg over the life of the plant and the PV hydrogen production produces at 4 to 5 USD per kg. The cost of storage for CFC is compared to other systems, including high-pressure GH2 and atmospheric LH2. The system is shown to provide the lowest costs for all these options at the grid scale, due to its higher capacity than high-pressure GH2 and ability to operate at 80K, receiving refrigeration from liquid nitrogen systems reducing capital and operating costs when compared LH2 storage systems. SMR is competitive with CCGT at the gas prices, both of which have lower LCOE than the PV system. When accounting for variability in gas prices, the PV and electrolyzer system is less sensitive to these changes and provides the lowest LCOE across the whole range.

08 HYDROGEN↗

Particle-based high-temperature thermochemical energy storage reactors

Solar and other renewable energy driven gas-solid thermochemical energy storage (TCES) technology is a promising solution for the next generation energy storage systems due to its high operating temperature, efficient energy conversion, ultra-long storage duration, and potential high energy density. Experimental and theoretical studies suggest that the respective gravimetric and volumetric TCES energy storage densities vary from 200 to 3000 kJ kg –1 and 1–3 GJ m –3 . Solar radiation or heat generated from electric furnaces powered by renewable electricity can be stored in the form of chemical energy through endothermic reactions, while the stored chemical energy can be converted to thermal energy via an exothermic reaction when needed. The design of highly effective reactors requires a deep understanding of materials, thermodynamics, chemical kinetics, and transport phenomena. At time of writing, TCES reactors are yet to be deployed at commercially relevant scales, leaving a substantial gap between development efforts and commercial feasibility. Therefore, this review aims to examine the state-of-the-art design and performance of particle-based TCES reactors with different reactive materials. Fundamentals related to TCES reactive materials, reaction conditions, thermodynamics and kinetics, and transport phenomena are reviewed in detail to provide a comprehensive understanding of the reactor design and operation. Five major types of TCES reactors have been comprehensively reviewed and compared, including fixed, moving, rotary, fluidized, and entrained bed reactors. Most reported prototype reactors in the literature operate at lab scale with thermal inputs below 40 kW, and scaled TCES reactors (e.g., at megawatt level) are yet to be demonstrated. The nominal reactor operating temperatures range from 300 to 1500 °C, depending on the selected chemistry, reactive material, and heat sources. To evaluate their designs, the reactors are assessed in aspects of performance, cost, and durability. Discrepancies in performance indicators of energy storage density, extent of reaction, and various energy efficiencies are highlighted. The scale-up of reactors and power block integration, which hold the key to the successful commercialization of TCES systems, are critically analyzed. Furthermore, advanced materials (both reactive materials and ceramic reactor housing materials), effective particle flow control, advanced modeling tools, and novel system design may bring significant improvement to the energy efficiency, storage density and cost competitiveness of particle-based TCES reactors.

25 ENERGY STORAGE↗

Ion accelerator system mounting design and operating characteristics for a 5 kW 30-cm xenon ion engine

Results from a series of experiments to determine the effect of accelerator grid mount geometry on the performance of the J-series ion optics assembly are described. Three mounting schemes, two flexible and one rigid, are compared for their relative ion extraction capability over a range of total accelerating voltages. The largest ion beam current, for the maximum total voltage investigated, is shown to occur using one of the flexible grid mounting geometries. However, at lower total voltages and reduced engine input power levels, the original rigid J-series ion optics accelerator grid mounts result in marginally better grid system performance at the same cold interelectrode gap.

Aston, Graeme↗

Connecting Energy Input With Ionospheric Upflow and Outflow

The connection between energy inputs and the generation of ion upflows and outflows is a topic of keen scientific interest and the subject of a number of empirical studies. Despite this interest, it remains uncertain how different ion species respond to energy input, what defines the upper and lower bounds of the ion flux, and what role solar illumination plays in regulating the relationship between energy input and ion upflows/outflows. This work simulates how ion flux scales with low and high altitude energization, and to a combination of both. Furthermore, we examine the influence of solar illumination on these relationships by considering how the scaling of ion flux with energy input changes over the solar cycle, comparing solar minimum and maximum, as well as how they change from day to night conditions. We find O -+ flux tends to respond more strongly to energy inputs than H -+ flux, with the O -+ flux often exhibiting a lower activation energy and a greater dynamic range. The lower bound of the ion flux at 4,000 km is typically defined by the polar wind H -+ , although O -+ upflows can dominate at low altitudes in the presence of significant frictional heating of the ion gas or soft electron precipitation. However, when significant soft electron precipitation and wave-particle interactions are present simultaneously the lower bound of the ion flux at 4,000 km is defined by the O -+ . Finally, we find a difference between the steady state response of the outflow to energy input and the peak response.

A. Glocer↗

Ares I-X First Flight Loss of Vehicle Probability Analysis

As part of the Constellation (Cx) Program development effort, several test flights were planned to prove concepts and operational capabilities of the new vehicles being developed. The first test, involving the Eastern Test Range, is the Ares I-X launched in 2009. As part of this test, the risk to the general public was addressed to ensure it is within Air Force requirements. This paper describes the methodology used to develop first flight estimates of overall loss of vehicle (LOV) failure probability, specifically for the Ares I-X. The method described in this report starts with the Air Force s generic failure probability estimate for first flight and adjusts the value based on the complexity of the vehicle as compared to the complexity of a generic vehicle. The results estimate a 1 in 9 probability of failure. The paper also describes traditional PRA methods used in this assessment, which were then combined with the updated first flight risk methodology to generate inputs required by the malfunction turn analysis to support estimate of casualty (Ec) calculations as part of the Final Flight Data Package (FFDP) delivered to the Eastern Range for Final Flight Plan Approval.

Bigler, Mark A.↗

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

Danovo Energy Solution's presented its paper named: Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events at the 2026 Georgia Tech Fault & Disturbance Analysis Conference. The full paper can be found at OSTI ID# 3169150 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danova Energy Solutions]↗

The dc arc characteristics in subsonic orifice nozzle flow

The cold air flow field for a 1/27 cm orifice nozzle was determined for subsonic flow velocities. In addition, d.c. arc voltage, current, and diameter measurements were made for a range of velocities and arc gaps. Average voltage gradients increased rapidly as an arc extinguishing velocity was approached. Measured values of current and diameter were used as an input for relaxation solution of an energy balance equation to compute radial temperature profiles. Calculated arc voltage gradients compare favorably with measured average voltage gradients.

Nagamatsu, H. T.↗

A model of Martian slope winds - Implications for eolian transport

Observations of dark Martian wind streaks not associated with visible topographic points of origin (coalesced dark streaks) show these features to favor regions with slopes of 1-10 deg. To investigate the circulation over such slopes, a Boussinesq fluid is adopted and a constant eddy diffusivity parameterization is assumed for small-scale mixing. The equations of motion are scaled to determine the range of slopes over which a strong local circulation due to slope winds can exist. For nighttime conditions, the estimated range compares well with the observed range of slopes favored by coalesced dark streaks. For daytime conditions, the slope wind solution is not valid. A simple one-dimensional analytic model is solved to determine friction velocities and velocity and temperature profiles. For reasonable choices of the input parameters, friction velocities and wind velocities suggestive of active downslope eolian transport on slopes of 1-10 deg are found. Friction velocities are largest over surfaces with low thermal inertia and large roughness length.

Magalhaes, J.↗

Gain-adaptive vector quantization for medium-rate speech coding

A class of adaptive vector quantizers (VQs) that can dynamically adjust the 'gain' of codevectors according to the input signal level is introduced. The encoder uses a gain estimator to determine a suitable normalization of each input vector prior to VQ coding. The normalized vectors have reduced dynamic range and can then be more efficiently coded. At the receiver, the VQ decoder output is multiplied by the estimated gain. Both forward and backward adaptation are considered and several different gain estimators are compared and evaluated. An approach to optimizing the design of gain estimators is introduced. Some of the more obvious techniques for achieving gain adaptation are substantially less effective than the use of optimized gain estimators. A novel design technique that is needed to generate the appropriate gain-normalized codebook for the vector quantizer is introduced. Experimental results show that a significant gain in segmental SNR can be obtained over nonadaptive VQ with a negligible increase in complexity.

Chen, J.-H.↗