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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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Report discusses development of minimum-complexity mathematical model of helicopter for use in flight simulator. Development motivated by computational delays, costs, long development times, and inflexibility of sophisticated models now in use. New model overcomes these disadvantages and provides better engineering understanding of those features pertaining to handling qualities apparent to pilot who uses simulator.
Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.
Report presents study of finite-element mathematical modeling as used in analyzing stresses and strains at joints between thin, shell-like components (e.g., ducts) and thicker components (e.g., flanges or engine blocks). First approach uses global/local model to evaluate system. Provides correct total response and correct representation of stresses away from any discontinuities. Second approach involves development of special transition finite elements to model transitions between shells and thicker structural components.
DTV-SIM is a computer program that implements a mathematical model of the flight dynamics of a missile-shaped drop test vehicle (DTV) equipped with a multistage parachute system that includes two simultaneously deployed drogue parachutes and three main parachutes deployed subsequently and simultaneously by use of pilot parachutes. DTV-SIM was written to support air-drop tests of the DTV/parachute system, which serves a simplified prototype of a proposed crew capsule/parachute landing system.
A previously developed mathematical model is amended to more accurately incorporate the effects of lift and drag on single dust particles in order to predict their behavior in the wake of high velocity gas flow. The model utilizes output from a CFD or DSMC simulation of exhaust from a rocket nozzle hot gas jet. An extension of the Saffman equation for lift based on the research of McLaughlin (1991) and Mei (1992) is used, while an equation for the Magnus force modeled after the work of Oesterle (1994) and Tsuji et al (1985) is applied. A relationship for drag utilizing a particle shape factor (phi = 0.8) is taken from the work of Haider and Levenspiel (1989) for application to non-spherical particle dynamics. The drag equation is further adjusted to account for rarefaction and compressibility effects in rarefied and high Mach number flows according to the work of Davies (1945) and Loth (2007) respectively. Simulations using a more accurate model with the correction factor (Epsilon = 0.8 in a 20% particle concentration gas flow) given by Richardson and Zaki (1954) and Rowe (1961) show that particles have lower ejection angles than those that were previously calculated. This is more prevalent in smaller particles, which are shown through velocity and trajectory comparison to be more influenced by the flow of the surrounding gas. It is shown that particles are more affected by minor changes to drag forces than larger adjustments to lift forces, demanding a closer analysis of the shape and behavior of lunar dust particles and the composition of the surrounding gas flow.
In 2022, there was a global resurgence of mpox, with different clinical-epidemiological features compared with previous outbreaks. Sexual contact was hypothesized as the primary transmission route, and the community of men having sex with men (MSM) was disproportionately affected. Because of the stigma associated with sexually transmitted infections, the real burden of mpox could be masked. We quantified the basic reproduction number (R 0 ) and the underestimated fraction of mpox cases in 16 countries, from the onset of the outbreak until early September 2022, using Bayesian inference and a compartmentalized, risk-structured (high-/low-risk populations) and two-route (sexual/non-sexual transmission) mathematical model. Machine learning (ML) was harnessed to identify underestimation determinants. Estimated R 0 ranged between 1.37 (Canada) and 3.68 (Germany). The underestimation rates for the high- and low-risk populations varied between 25–93% and 65–85%, respectively. The estimated total number of mpox cases, relative to the reported cases, is highest in Colombia (3.60) and lowest in Canada (1.08). In the ML analysis, two clusters of countries could be identified, differing in terms of attitudes towards the 2SLGBTQIAP+ community and the importance of religion. Given the substantial mpox underestimation, surveillance should be enhanced, and country-specific campaigns against the stigmatization of MSM should be organized, leveraging community-based interventions.
Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.
A mathematical model, termed the Slug Loss Model, has been developed for describing thermal capacitance (slug) calorimeter behavior when heat losses and other decaying processes are not negligible. This model results in the temperature time slope taking the mathematical form of exponential decay. When data is found to fit well to this model, it allows a heat flux value to be calculated that corrects for the losses and may be a better estimate of the cold wall fully catalytic heat flux, as is desired in arc jet testing. The model was applied to the data from a copper slug calorimeter inserted during a particularly severe high heating rate arc jet run to illustrate its use. The Slug Loss Model gave a cold wall heat flux 15% higher than the value of 2,250 W/sq cm obtained from the conventional approach to processing the data (where no correction is made for losses). For comparison, a Finite Element Analysis (FEA) model was created and applied to the same data, where conduction heat losses from the slug were simulated. The heat flux determined by the FEA model was found to be in close agreement with the heat flux determined by the Slug Loss Model.
There is growing interest in the development of Li-metal-based solid state batteries, driven by their promise in improving the energy density to satisfy electric vehicle requirements. In this work, we examine the status of Solid polymer electrolytes (SPEs) based solid state batteries for electric vehicle applications using a continuum scale mathematical model. We examine LiFePO4(LFP) cathode/lithium metal anode batteries containing three different electrolytes, namely (1) a liquid electrolyte, (2) the polystyrene-b-poly(ethylene oxide) (SEO) block copolymer electrolyte, and (3) a single-ion conducting (SIC) block copolymer electrolyte, with the liquid electrolyte serving as the baseline for the comparison. By using an optimization procedure, we assemble "virtual" batteries to identify the optimal design that maximizes energy density while allowing the power requirements of electric vehicles (EVs) to be satisfied. Results show the present status of different SPEs are still below what is considered acceptable and further improvements are needed to achieve electric vehicle targets. The optimization studies conducted here show that for low transference number electrolytes (similar to 0.2) the conductivity target is 5 x 10(-3)S cm(-1), while for a unity transference number electrolyte this target decreases to 4 x 10(-4)S cm(-1). These targets provide guidance for polymer synthesis researchers to develop better polymers for use in EVs.
Presented herein is a parametric study of the defining equations which govern the steady state operational characteristics of the Grumman Monogroove Dual Passage Heat Pipe. These defining equations are combined to develop a mathematical model which describes and predicts the operational and performance capabilities of a specific heat pipe, given the necessary physical characteristics and working fluid. Included is a brief review of the current literature, a discussion of the governing equations, and a description of both the mathematical and computer model. Final results of preliminary test runs of the model are presented and compared with experimental tests performed by Grumman on actual prototypes.
A parametric study of the defining equations which govern the steady state operational characteristics of the Grumman monogroove dual passage heat pipe is presented. These defining equations are combined to develop a mathematical model which describes and predicts the operational and performance capabilities of a specific heat pipe given the necessary physical characteristics and working fluid. Included is a brief review of the current literature, a discussion of the governing equations, and a description of both the mathematical and computer model. Final results of preliminary test runs of the model are presented and compared with experimental tests on actual prototypes.
An abbreviated version of a mathematical model of the steady state in isoelectric focusing is presented. Details of the mathematical transformations leading to a model suitable for computer implementation and numerical solution are given in the Appendix. The model describes the structure of concentration, pH, conductivity and potential gradients arising from the focusing of electrochemically defined ampholytes. Some of the results of computer simulations of two and three component systems are of particular interest to the experimentalist and are presented together with experimental validation of this model.
Full function hydrogen stations are a reality; fuel cell electric vehicle drivers can pull up to commercial fueling stations and receive 3–5 kg in less than 5 min, for an approximately 300-mile range. The demand for hydrogen is increasing, driven by an increase in the fueling of public and private fuel cell vehicles. This study describes the development and value of a model that simulates stochastic future demand at a hydrogen filling station. The predictive hydrogen demand model described in this article is trained from mathematical models constructed from actual hydrogen fill count, amount, and frequency data. Future fill probabilities inform the hour-by-hour demand profile and the station state of either “available, ready to fill” or “available, filling”. For example, a prediction for a station generally dispensing 5,000 kg a week on a Friday afternoon at 4 p.m. is 16 fills, totaling 48.7 kg, with a 0.52 proportion of time spent in “available, filling” state yielding 31 min of filling time. This is a first-of-its kind, published study on predicting future hydrogen demand by the time of day (e.g., hour-by-hour intervals) and day of week. This study can be used for hydrogen station requirements and operation and maintenance strategies and to assess the impact of demand variations and scenarios. Finally, this article presents the current status of hydrogen demand, the model development methods, a set of sample results. Discussion and conclusions concentrate on the value and use of the proposed model.
Lack of harmonic rich datasets limits the ability to have fine grained load models at grid edge. We aim to develop mathematical models for power electronic based load combinations at grid edge to help replicate current and future evolving load conditions
Dynamic Analysis Program, FORTRAN 4 Level H /DAP4H/, developed from 27 subprograms, features liberal use of the subroutines, subprograms, and skeletonization to minimize programming effort in formulating models of new systems and components. It formulates mathematical models of complex mechanical, pneumatic, and hydraulic dynamic systems.
Special modeling techniques were developed to simulate an accurate mathematical model of the transporter/canister/payload system during ground transport of the Inertial Upper Stage/Tracking and Data Relay Satellite (IUS/TDRS) payload. The three finite element models - the transporter, the canister, and the IUS/TDRS payload - were merged into one model and used along with the NASTRAN normal mode analysis. Deficiencies were found in the NASTRAN program that make a total analysis using modal transient response impractical. It was also discovered that inaccuracies may exist for NASTRAN rigid body modes on large models when Given's method for eigenvalue extraction is employed. The deficiencies as well as recommendations for improving the NASTRAN program are discussed.
Capillary Pumped Loop (CPL) Modeler computer program is amalgamation of software that mathematically models performance of CPL system and its environment. Two-phase heat-transport device capable of transferring heat loads efficiently over large distance with little temperature differential. Utilizes surface-tension forces established in fine-pore capillary wick to circulate working fluid, requiring no external pumpling power. Predicts steady-state or quasi-steady behavior of CPL embedded in spacecraft or other thermal environment. Also predicts location of liquid/vapor interface in each condenser. Written in VAX/VMS FORTAN 77.
NASA has been interested in the development of methods for evaluating the predictive accuracy of structural dynamic models. This interest stems from the use of mathematical models in evaluating the structural integrity of all spacecraft prior to flight. Space structures are often too large and too weak to be tested fully assembled in a ground test lab. The predictive accuracy of a model depends on the nature and extent of its experimental verification. The further the test conditions depart from in-service conditions, the less accurate the model will be. Structural damping is known to be one source of uncertainty in models. The uncertainty in damping is explored in order to evaluate the accuracy of dynamic models. A simple mass-spring-dashpot system is used to illustrate a comparison among three methods for propagating uncertainty in structural dynamics models: the First Order Method, the Numerical Simulation Method, and the Fuzzy Set Method. The Fuzzy Set Method is shown to bound the range of possible responses and thus to provide a valuable limiting check on the First Order Method near resonant conditions. Fuzzy Methods are a relative inexpensive alternative to numerical simulation.