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At least 487 records · Page 27

Distinguishing between CAT and non-CAT areas by use of discriminant function analysis

The investigation considered is concerned with a method in which a statistical approach is employed to determine algebraic functions involving selected synoptic-scale parameters which would indicate areas and altitudes of CAT in the stratosphere over the western U.S. The statistical approach selected is based on discriminant function analysis. The functions are determined from combinations of synoptic-scale parameters and stratospheric turbulence data. It was found in the investigation that there is a relationship between selected combinations of synoptic-scale parameters of the upper troposphere and lower stratosphere and stratospheric clear-air turbulence.

Clark, T. L.↗

Indirect synthesis of multidegree-of-freedom transient systems

The indirect synthesis method is developed and shown to be capable of leading a near-optimal design of multidegree-of-freedom and multidesign-element transient nonlinear dynamical systems. The basis of the approach is to select the open design parameters such that the response of the portion of the system being designed approximates the limiting performances solution. The limiting performance problem can be formulated as one of linear programming by replacing all portions of the system subject to transient disturbances by control forces and supposing that the remaining portions are linear as are the overall kinematic constraints. One then selects the design parameters that respond most closely to the limiting performance solution, which can be achieved by unconstrained curve-fitting techniques.

Chen, Y. H.↗

Physical and dynamical conditions in interstellar clouds

Techniques for measuring the local and global parameters that describe molecular clouds are presented and illustrated by selected results. The local parameters which characterize a given location in a cloud are gas kinetic temperature, dust temperature, total density, magnetic field strength, abundance of species i, volume cooling and heating rates for gas and dust, and the thermal and turbulent velocities. Global properties which characterize the cloud as a whole include the size expressed as a length or area, the orientation and shape, the mass, and the integrated heating and cooling rates. If the cloud as a whole is collapsing or rotating, then the collapse velocity and the rotational velocity or angular momentum are global properties. An intermediate class of parameters which shares features of local and global properties includes the column density of species i, the total column density, and the average density.

Evans, N. J., II↗

Bayesian inference in geomagnetism

The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.

Backus, George E.↗

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗

Analysis of the passive stabilization of the long duration exposure facility

The nominal Long Duration Exposure Facility (LDEF) configurations and the anticipated orbit parameters are presented. A linear steady state analysis was performed using these parameters. The effects of orbit eccentricity, solar pressure, aerodynamic pressure, magnetic dipole, and the magnetically anchored rate damper were evaluated to determine the configuration sensitivity to variations in these parameters. The worst case conditions for steady state errors were identified, and the performance capability calculated. Garber instability bounds were evaluated for the range of configuration and damping coefficients under consideration. The transient damping capabilities of the damper were examined, and the time constant as a function of damping coefficient and spacecraft moment of inertia determined. The capture capabilities of the damper were calculated, and the results combined with steady state, transient, and Garber instability analyses to select damper design parameters.

Siegel, S. H.↗

Updating the Space Communications and Navigation (SCaN) Link Tool Executable Software to Version 5

NASA’s Space Communications and Navigation (SCaN) program is responsible for providing space communication channels in low Earth orbit, geosynchronous orbit, and deep space for a variety of space missions. The SCaN Link Tool is a standalone, executable, and personal computer (PC)-based software operated via a user interface, which provides NASA civil servants and contractors, as well as the public by way of the tool’s inclusion in the NASA Software Catalog, with in-depth satellite communications link analysis capability. Version 4 of the tool was built using PythonTM (Python Software Foundation) with the help of libraries such as NumPy and SciPy for numerical calculations, Matplotlib for graphical visualizations, and PyQt5 for the graphical user interface. It utilizes radiofrequency (RF) and optical communications link analysis calculations to give users the ability to input known link parameters and calculate select link performance outputs. With the development of the next-generation architecture for space satellite communications in the coming decade, NASA will benefit by having more in-depth communications link analysis tools at its disposal. The tool’s update from version 4 to version 5 aims to provide higher output value accuracy, the ability to solve for a more diverse set of output variables, as well as analog and digital repeater capabilities. Options included in the tool’s functionality, such as the ability to save configuration parameter values, graphs, and results, as well as the provision of default parameter values, increase the tool’s versatility. Users will have access to in-depth, accurate communications link analysis as more advanced satellite constellations are designed and deployed by NASA and the growing commercial aerospace community.

Green, Jack L.↗

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints. Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

17 WIND ENERGY↗

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗

Engine selection for transport and combat aircraft

The procedures that are used to select engines for transport and combat aircraft are discussed. In general, the problem is to select the engine parameters including engine size in such a way that all constraints are satisfied and airplane performance is maximized. This is done for four different classes of aircraft: (1) a long haul conventional takeoff and landing (CTOL) transport, (2) a short haul vertical takeoff and landing (VTOL) transport, (3) a long range supersonic transport (SST), and (4) a fighter aircraft. For the commercial airplanes the critical constraints have to do with noise while for the fighter, maneuverability requirements define the engine. Generally, the resultant airplane performance (range or payload) is far less than that achievable without these constraints and would suffer more if nonoptimum engines were selected.

Dugan, J. F., Jr.↗

Comparison of soil dielectric mixing models for Soil Moisture Retrieval using SMAP Brightness Temperature over croplands in India

The accurate estimation of soil moisture (SM) using microwave remote sensing depends mostly on careful selection of retrieval parameters among which the soil dielectric mixing model is the important one. These models are often categorized into empirical, semi-empirical or volumetric based on their methodologies and input data requirements. To study in detail, the comparative performance of four dielectric mixing models -- Wang & Schmugge model, Hallikainen model, Dobson model and Mironov model were used with Soil Moisture Active Passive (SMAP) L-band brightness temperature and Single Channel Algorithm for SM retrieval over agricultural landscapes in India. The highest performance statistics combination in terms of Root Mean Square Error (RMSE), correlation coefficient (R^(2)) and percentage bias (PBIAS) against the concurrent in-situ SM measurements were calculated at the selected validation sites. The overall results indicate that the best performance was given by the Mironov model (RMSE = 0.07 cu. m/cu. m), followed by Wang & Schmugge model (RMSE = 0.08 cu. m3/cu. m), Hallikainen model (RMSE = 0.09 cu. m/cu. m), Dobson model (RMSE = 0.10 cu. m/cu. m) and original SMAP radiometer SM (RMSE = 0.12 cu. m/cu. m). Findings of this study provides important insights into application and performance of dielectric mixing models in mapping surface SM variations. This study also underlines the pivotal role of local conditions for SM retrieval which should be carefully included in the algorithms.

Swati Suman↗

On the Relationship Between Transit Velocity of Interplanetary Shocks and Solar Active Processes

Recently, it was reported that preferential relationships exist between the transit velocity V(sub T) of earthward-directed interplanetary shocks and solar active processes, in particular, eruptive filaments outside active regions (the size of the erupting filament L(sub f)) and solar flares (the value of the X-ray characteristic J). Unfortunately, statistical testing of the proposed associations was not accomplished, nor was the 'geo-effectiveness' of the events adequately described. Reported here are the results of a re-examination of the 21 eruptive filaments (SSC-EF events) and 26 X-ray flares (SSC-F events) that have been associated with storm sudden commencements (SSCs) at Earth. Simple statistical testing refutes the claim that a preferential relationship exists between V(sub T) and L(sub F), while it supports the claim that one exists between V(sub T) and J. More importantly, the inferred relationship between V(sub T) and J is found to be more complicated than previously thought. In particular, it now appears that SSC-F events may be separable into two groups, based on the value of J: a low-J group (J less than 56), in which V(sub T) varies directly with J, and a high-J group (J greater than 56), in which V(sub T) varies inversely with J. As a whole, high-J events are associated with shocks of higher average transit velocity than those of low-J events, and SSC-F events with shocks of higher average transit velocity than those of SSC-EF events. Further, high-J events tend to be of greater X-ray class ( greater than M3), longer duration (greater then 80 min), and are more likely to be associated with type II/IV radio emission (9 of 12) than low-J events. They also tend to occur in magnetically complex (gamma/delta configuration) active regions (10 of 12) that are large in area extent (area greater than 445 millionths of a solar hemisphere) on the day of flaring (9 of 12). Of the 9 solar proton events that affected the Earth's environment that were found to be associated with SSC-F events, six were high-J events. Concerning 'geo-effectiveness', there appears to be no preferential relationship between the value of the J-parameter and the most negative value of the Dst geomagnetic index Dst(min) following the SSC, which is found to usually occur at 6-14 h after SSC onset (18 of 26) and which ranged in value from -1 to -249 (having a median value of about -75). Of the 26 SSC-F events, only 14 can be associated with a Dst(min) less than or equal to -75, and of these only 7 were high-J events. Of the 14 storm-related events (i.e. Dst(min) less than or equal to -75), three have previously been identified as being either 'magnetic clouds' or 'bidirectional flows', both manifestations of earthward-directed coronal mass ejections (CMEs). Superposed epoch analyses of selected solar wind parameters and Dst during the interval of storm-related SSC-F events demonstrate that geoeffective SSC-F events tend to be associated with solar wind flows that are faster, greater in magnetic field strength, and have a rotating field which has a strong southward component shortly after SSC onset, in comparison to SSC-F events that do not have Dst(min) less than or equal to 75. Therefore, it is inferred that geoeffective SSC-F events are probably fast earthward-directed CMEs. Although no single parameter is found that can serve as a predictor of high-skill level for determining the geoeffectiveness of an SSC-F event prior to its occurrence at Earth, one finds that knowledge of the flare's hemispheric location and appearance or lack of appearance of a two-ribbon structure is sufficient to correctly predict the geoeffectiveness of 20 out of 25 of the SSC-F events (80%). Surprisingly, the association or lack of association of metric type II/IV radio emission as a characteristic for determining the geoeffectiveness of the SSC-F events proved unfruitful, as did, to a lesser extent, the duration of the X-ray emission.

Wilson, Robert M.↗

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗

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↗

Development of a parameter optimization technique for the design of automatic control systems

Parameter optimization techniques for the design of linear automatic control systems that are applicable to both continuous and digital systems are described. The model performance index is used as the optimization criterion because of the physical insight that can be attached to it. The design emphasis is to start with the simplest system configuration that experience indicates would be practical. Design parameters are specified, and a digital computer program is used to select that set of parameter values which minimizes the performance index. The resulting design is examined, and complexity, through the use of more complex information processing or more feedback paths, is added only if performance fails to meet operational specifications. System performance specifications are assumed to be such that the desired step function time response of the system can be inferred.

Whitaker, P. H.↗

SP-100 space nuclear power system

A baseline design concept for a 100 kWe nuclear reactor space power system is described. The concept was developed under contract from JPL as part of a joint program of the DOE, DOD, and NASA. The major technical and safety constraints influencing the selection of reactor operating parameters are discussed. A lithium-cooled compact fast reactor was selected as the best candidate system. The material selected for the thermoelectric conversion system was silicon germanium (SiGe) with gallium phosphide doping. Attention is given to the improved safety of the seven in-core control rod configuration.

Given, R. W.↗

Sensitivity of an atmospheric photochemistry model to chlorine perturbations including consideration of uncertainty propagation

Models of stratospheric photochemistry are generally tested by comparing their predictions for the composition of the present atmosphere with measurements of species concentrations. These models are then used to make predictions of the atmospheric sensitivity to perturbations. Here the problem of the sensitivity of such a model to chlorine perturbations ranging from the present influx of chlorine-containing compounds to several times that influx is addressed. The effects of uncertainties in input parameters, including reaction rate coefficients, cross sections, solar fluxes, and boundary conditions, are evaluated using a Monte Carlo method in which the values of the input parameters are randomly selected. The results are probability distributions for present atmosheric concentrations and for calculated perturbations due to chlorine from fluorocarbons. For more than 300 Monte Carlo runs the calculated ozone perturbation for continued emission of fluorocarbons at today's rates had a mean value of -6.2 percent, with a 1-sigma width of 5.5 percent. Using the same runs but only allowing the cases in which the calculated present atmosphere values of NO, NO2, and ClO at 25 km altitude fell within the range of measurements yielded a mean ozone depletion of -3 percent, with a 1-sigma deviation of 2.2 percent. The model showed a nonlinear behavior as a function of added fluorocarbons. The mean of the Monte Carlo runs was less nonlinear than the model run using mean value of the input parameters.

Stolarski, R. S.↗

Enhancing the cooling performance of thermocouples: a power-constrained topology optimization procedure

Abstract Heat pumping through thermoelectric devices has many advantages over traditional cooling. However, their current efficiency is a limiting factor in their implementation. In this paper, we approach the non-convex topology optimization of thermoelectrical elements for cooling applications through the method of moving asymptotes (MMA) to improve their cooling capabilities per watt usage. The optimization problem is defined for a given power budget, aiming for the minimum temperature with a known heat pumping need. The introduction of power as a constraint justifies the introduction of the voltage gradient across the thermocouple as a design variable to maintain the thermoelectrical device in its optimum power-to-heat extraction ratio. To better understand the convergence of this non-convex problem, we present a two-variable analytical thermoelectric optimization model. This example provides information on how to select the penalty parameters used to scale the three material coefficients involved in the problem to obtain lower objective values and better convergence using MMA. The analytical model shows the non-convexity of the problem and provides the recommendation to use penalization coefficients of the form $$p_k=p_{\sigma }>p_{\alpha }=1$$ p k = p σ > p α = 1 for the thermal conductivity, electrical conductivity, and Seebeck coefficients. We tested these penalization coefficients through optimizations of a model based on the 1MC10-031 commercial thermoelectric-cooler (TEC) using the finite element method (FEM). These penalization coefficients provided local minima without the need for volume constraints. With this procedure, we found designs that provided temperatures close to 10 degrees lower using 60% less semiconductor material volume compared to the initial design.

Gutiérrez, G. Reales↗