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At least 37 records · Page 2

Evidence for mass-loading of the Venus magnetosheath

The observed magnetic field configuration in the Venus magnetosheath contains information about the solar wind mass-loading processes occurring as a result of the extension of the neutral atmosphere into the magnetosheath. In this paper, magnetic field signatures of various mass-loading processes are discussed and experimental results from the Pioneer Venus Orbiter magnetometer experiment are examined for evidence of these signatures. The data suggest that the -V(bar)XB(bar) acceleration process, stochastic pickup of ionospheric ions, and J(bar)XB(bar) force 'scavenging' at the ionopause all occur at various times.

Luhmann, J. G.↗

Statistical load data processing

A recorder system has been installed on two operational fighter aircrafts. Signal values from a c.g.-acceleration transducer and a strain-gage installation at the wing root were sampled and recorded in digital format on the recorder system. To analyse such load-time histories for fatigue evaluation purposes, a number of counting methods are available in which level crossings, peaks, or ranges are counted. Ten different existing counting principles are defined. The load-time histories are analysed to evaluate these counting methods. For some of the described counting methods, the counting results might be affected by arbitrarily chosen parameters such as the magnitude of load ranges that will be neglected and other secondary counting restrictions. Such influences might invalidate the final counting results entirely. The evaluation shows that for the type of load-time histories associated with most counting methods, a sensible value of the parameters involved can be found.

Vandijk, G. M.↗

LDEXPT, an intelligent database system for the Composite Load Spectra project

The Composite Load Spectra project develops probabilistic models to simulate the probabilistic loads for selected components of a generic space propulsion system. Tremendous information such as engine load variables and their distributions is needed by the simulation program. An intelligent data base system was constructed and integrated with the probabilistic load simulation program to manage and maintain the knowledge base of the Composite Load Spectra project. The intelligent data base system takes care of the data retrieval and storage functions and has expert knowledge on engine load models and associated engine variables. The integration of the intelligent data base into the load simulation program achieves a smooth coupling between the numeric processing (load simulation calculation) and the symbolic processing (intelligent load information management).

Ho, H.↗

Identification Uncertainty in Inverse Material Model Parameter Determination: A Sensitivity‐Based Decision Process for Load Path Selection

This research proposes a sensitivity-based framework for selecting the optimal prescribed loading path for a biaxial cruciform specimen. Optimality here is determined by the direction and magnitude of the prescribed displacement that minimizes the influence of random noise on the material model parameter identification. Using simulated experimental data based on finite element simulation, in this work, we identify the material model parameters of a Ludwik hardening model and plane stress implementation of the Hill-48 yield criterion using finite element model updating (FEMU). Our analysis reveals that the identification (or estimator) uncertainty of model parameters depends on the displacement boundary conditions (i.e., loading sequence) and the ground-truth value of the individual parameters. Optimal experimental design (OED) criteria based on the Fisher information matrix were investigated to mitigate indecision in the choice of optimal load path when the identification uncertainty of different material model parameters optimized at different load paths. The determinant of the Fisher information matrix was chosen here as the more useful metric due to its ability to capture uncertainty of the most influential material model parameters. The proposed framework demonstrates potential for real-time automated load step selection using scalar criteria derived prior to mechanical loading. The framework can be generalized to other geometries, boundary conditions and material models, allowing this procedure to be utilized for different experimental configurations and materials.

Fayad, Samuel S. [University of Illinois at Urbana↗

Rapid Corner Detection Using FPGAs

In order to perform precision landings for space missions, a control system must be accurate to within ten meters. Feature detection applied against images taken during descent and correlated against the provided base image is computationally expensive and requires tens of seconds of processing time to do just one image while the goal is to process multiple images per second. To solve this problem, this algorithm takes that processing load from the central processing unit (CPU) and gives it to a reconfigurable field programmable gate array (FPGA), which is able to compute data in parallel at very high clock speeds. The workload of the processor then becomes simpler; to read an image from a camera, it is transferred into the FPGA, and the results are read back from the FPGA. The Harris Corner Detector uses the determinant and trace to find a corner score, with each step of the computation occurring on independent clock cycles. Essentially, the image is converted into an x and y derivative map. Once three lines of pixel information have been queued up, valid pixel derivatives are clocked into the product and averaging phase of the pipeline. Each x and y derivative is squared against itself, as well as the product of the ix and iy derivative, and each value is stored in a WxN size buffer, where W represents the size of the integration window and N is the width of the image. In this particular case, a window size of 5 was chosen, and the image is 640 480. Over a WxN size window, an equidistance Gaussian is applied (to bring out the stronger corners), and then each value in the entire window is summed and stored. The required components of the equation are in place, and it is just a matter of taking the determinant and trace. It should be noted that the trace is being weighted by a constant k, a value that is found empirically to be within 0.04 to 0.15 (and in this implementation is 0.05). The constant k determines the number of corners available to be compared against a threshold sigma to mark a valid corner. After a fixed delay from when the first pixel is clocked in (to fill the pipeline), a score is achieved after each successive clock. This score corresponds with an (x,y) location within the image. If the score is higher than the predetermined threshold sigma, then a flag is set high and the location is recorded.

Morfopoulos, Arin C.↗

Optimization and understanding of ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalyst for enhanced CO 2 -methanol conversion at low temperature and pressure

Cu-ZnO-Al 2 O 3 is the most widely applied catalyst for CO 2 hydrogenation to methanol. However, it is still a challenge to produce methanol using this catalyst under low-temperature (<250 °C) and low-pressure (<10 bar) conditions with desirable yield and selectivity. In this work, by tuning the experimental processing parameters such as solvent, loading amount, and annealing temperature, highly improved ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalysts have been successfully demonstrated. Here, by using organic solvent (N,N-dimethylformamide (DMF), acetone, or isopropanol) for dip-coating loading process instead of deionized (DI) water, Cu-ZnO-Al 2 O 3 nanocatalysts was comparatively better dispersed on the nanorod array support with populated and abundant active sites, thus enhancing the methanol yield. With the control of the loading amount and annealing temperature, finely distributed Cu nanoparticles were obtained on the ZnO nanorod surfaces to enhance the interactions between Cu and ZnO nanorod surfaces. Further improvement of the catalyst performance is demonstrated by tuning the reaction space velocity. At 200 °C and 10 bar conditions, the optimized catalyst achieved a methanol yield of 6.46 mol h –1 kg –1 with 100 % selectivity. The good stability after prolonged testing of the catalysts demonstrates the potential practical implementation. The in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements under the 1 bar reveal that the CO 2 hydrogenation to methanol on the ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalyst follows the CO reaction pathway, due to the surface oxygen vacancies on ZnO nanorods which facilitate CO 2 dissociation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Impact of remote sensing upon the planning, management, and development of water resources

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

Castruccio, P. A.↗

EV Charging Infrastructure Energization: An Overview of Approaches for Simplifying Processes and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure and electricity. Growth in electricity demand from EV charging, coupled with growth in other sectors like data centers and electrification of other sectors, is impacting electricity infrastructure and load service request processes after two decades of relatively flat electricity demand. While most electric vehicle charging occurs at home, enroute and depot charging for medium and heavy-duty vehicles, both using high-powered EV charging, are critical to meet electric vehicle operational needs. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have expressed distress that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions.

33 ADVANCED PROPULSION SYSTEMS↗

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of a bench-scale dissolution concept for the direct extraction of nuclear fuel

Current used nuclear fuel reprocessing efforts utilize a hydrometallurgical approach in which the UNF is dissolved in hot nitric acid followed by solvent extraction into an organic solvent to harvest target nuclides. Previous studies have shown that the dissolution and loading process could be combined into a single organic dissolution/extraction step, producing loaded organic in a single step process. This single step process also includes the advantage of selectively targeting key nuclides in the dissolution while leaving undesirable constituents as part of the undissolved solids. This process is referred to hereafter as direct extraction. Ongoing research from multiple national labs has proven the effectiveness of this technique at research scale. Therefore, potential methods to implement direct extraction at both bench and industrial scale have been developed. The key features of potential dissolver system designs were identified via the team at Pacific Northwest National Laboratory and several designs based on industrial counterparts were assessed for feasibility. This report summarizes the advantages and disadvantages of multiple methods, concluding with a path forward to create multiple unique dissolver designs. The first design will be a single stage recirculating eductor mixer. The second design recommendation is a stator rotor static mixing flow loop design. Each dissolver could be utilized separately, simultaneously, or in series to answer questions surrounding reaction kinetics including residence time, provide a proof of concept for targeted extractions of specific nuclides, and inform needs for industrial scale implementation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Path dependence of J in three numerical examples

Three cracked geometries are studied with the aid of a new finite element model. The procedure employs a variable singularity at the crack tip that tracks changes in the material response during the loading process. Two of the problems are tension-loaded center-crack panels and the other is a three-point bend specimen. Results usually agree with other numerical and analytical analyses, except the finding that J is path dependent as a substantial plastic zone develops. Credible J values are obtained near the crack tip and J shows a significant increase as the radius of J path increases over two orders of magnitude. Incremental and deformation theories are identical provided the stresses exhibit proportionality found in the far field stresses but not near the tip.

Karabin, M. E., Jr.↗

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

Mass loading at Titan and comets

Present understanding of the cometary mass loading process (the addition of newborn ions to high speed magnetized plasma flows) is explored and the cometary lesson is applied to the environment of Titan. Mass loading is the dominant physical process controlling the interaction of the solar wind with comets, and it might play an important role in the interaction of Titan's neutral torus and exosphere with Saturn's magnetosphere. Freshly born ions follow cycloidal trajectories, resulting from the superposition of gyration and E/B drift. In the plasma frame, the resulting velocity space distribution is a ring beam distribution at comets and a ring distribution at Titan. This difference in free energy is expected to generate significantly different levels of low frequency broad band electromagnetic turbulence and, thus, result in important differences in the implanted ion distributions. It is predicted that mass loading creates a hot, equatorially trapped plasma population at Titan.

Gombosi, Tamas I.↗

Challenges in Postprocessing of Hybrid Manufacturing of Magnet Polymer Composites to Enhance the Energy Product of NdFeB Bonded Magnets

Bonded permanent magnets need to process magnetic filler particles and binder together which is a form of hybrid or composite manufacturing that needs to simultaneously process multimaterials. Polymer bonding of the permanent magnets decreases the energy product of the bonded magnets which varies with square of loading fraction of magnetic materials. However, due to high viscosity of bonding polymer prohibits loading higher than 80 volume % of magnetic materials in most efficient loading process such as compression molding. To further increase the loading of magnetic fraction in the bonded permanent magnets, it is expected to be beneficial to introduce a fraction of nonreacting thermally sacrificial polymer along with permanent bonding polymer in the least permissible of about 20 volume % of the polymer. This process of first adding the sacrificial polymer for higher processability for composites and later removing it via post processing such as heat treatment provides a simple example of inclusion of both the additive and the subtractive stages of hybrid manufacturing. These hybrid composite magnets can be heat treated to remove the sacrificial polymer to further increase the density and energy product which might require to implement hot isostatic pressing for compaction. Although the identification of such ideal polymer requires an extensive polymer chemistry research, we have compression molded several permanent bonding polymers such as nylon, polycarbonate (PC) and polyphenyl sulfide (PPS) and potential sacrificial polymer such as polyoxymethylene (POM), polystyrene (PS), and Acrylonitrile Butadiene Styrene (ABS) and heat treated to remove the sacrificial polymers. It is discovered that oxygen free low temperature pyrolizable polymers could be the potential candidates for increasing the magnet particles loading for achieving high energy products.

36 MATERIALS SCIENCE↗

A Commercial Building Plug Load Management System that Uses Internet of Things Technology to Automatically Identify Plugged-In Devices and Their Locations

Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC's dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS's primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparison of the Effects of Tool Geometry for Friction Stir Welding Thin Sheet Aluminum Alloys for Aerospace Applications

In this presentation, the results of a recent study on the effect of pin tool design for friction stir welding thin sheets (0.040") of aluminum alloys 2024 and 7075 are provided. The objective of this study was to investigate and document the effect of tool shoulder and pin diameter, as well as the presence of pin flutes, on the resultant microstructure and mechanical properties at both room temperature and cryogenic temperature. Specifically, the comparison between three tools will include: FSW process load analysis (tool forces required to fabricate the welds), Static Mechanical Properties (ultimate tensile strength, yield strength, and elongation), and Process window documenting the range of parameters that can be used with the three pin tools investigated. All samples were naturally aged for a period greater than 10 days. Prior research has shown 7075 may require post weld heat treatment. Therefore, an additional pair of room temperature and cryogenic temperature samples was post-weld aged to the 7075-T7 condition prior to mechanical testing.

Merry, Josh↗