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At least 55 records · Page 3

Structure-property relationships and recyclability of natural fiber insulation

Thermal insulation can significantly decrease the energy required to maintain internal temperatures within buildings, saving money and decreasing environmental impacts. Many industrially available insulation options utilize petroleum-derived materials, such as polyurethane, fiberglass, and polystyrene, which can be detrimental to the environment by emitting greenhouse gases during production. A sustainable alternative to these synthetic insulations is the use of renewable feedstocks to produce comparable insulation products. In this work, natural fibers such as flax and banana were bound with an epoxy system to produce natural-fiber insulation. Key experimental parameters for this study included evaluating the fiber lengths and processing methods while varying the viscosity of the epoxy binder solvent dissolution. Insulation performance was determined by comparing density, thermal conductivity, resilience, and compressive strength; these parameters were tested to further understand and investigate the structure- property relationships within the system and to understand how these composites compare to current commercial materials. Furthermore, from this characterization and optimization, a natural fiber sample with an R/in. >5 was achieved, making these materials competitive with commercial alternatives.

Compressive strength↗

The analysis and modeling of dilatational terms in compressible turbulence

It is shown that the dilatational terms that need to be modeled in compressible turbulence include not only the pressure-dilatation term but also another term - the compressible dissipation. The nature of these dilatational terms in homogeneous turbulence is explored by asymptotic analysis of the compressible Navier-Stokes equations. A non-dimensional parameter which characterizes some compressible effects in moderate Mach number, homogeneous turbulence is identified. Direct numerical simulations (DNS) of isotropic, compressible turbulence are performed, and their results are found to be in agreement with the theoretical analysis. A model for the compressible dissipation is proposed; the model is based on the asymptotic analysis and the direct numerical simulations. This model is calibrated with reference to the DNS results regarding the influence of compressibility on the decay rate of isotropic turbulence. An application of the proposed model to the compressible mixing layer has shown that the model is able to predict the dramatically reduced growth rate of the compressible mixing layer.

Sarkar, S.↗

The analysis and modelling of dilatational terms in compressible turbulence

It is shown that the dilatational terms that need to be modeled in compressible turbulence include not only the pressure-dilatation term but also another term - the compressible dissipation. The nature of these dilatational terms in homogeneous turbulence is explored by asymptotic analysis of the compressible Navier-Stokes equations. A non-dimensional parameter which characterizes some compressible effects in moderate Mach number, homogeneous turbulence is identified. Direct numerical simulations (DNS) of isotropic, compressible turbulence are performed, and their results are found to be in agreement with the theoretical analysis. A model for the compressible dissipation is proposed; the model is based on the asymptotic analysis and the direct numerical simulations. This model is calibrated with reference to the DNS results regarding the influence of compressibility on the decay rate of isotropic turbulence. An application of the proposed model to the compressible mixing layer has shown that the model is able to predict the dramatically reduced growth rate of the compressible mixing layer.

Sarkar, S.↗

Lossy Compression: An Online Multi-Stage Technology for High-Fidelity Synchro- Waveform Measurements

Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency disturbances and transient phenomena. However, due to limitations in high-speed measurements and network bandwidth, it is challenging to transfer all high-fidelity synchro-waveforms losslessly and successfully. To cope with these challenges, a hybrid-based online multi-stage compression algorithm is proposed to significantly improve the compression efficiency for synchro-waveform measurements. Initially, the multiple discrete Wavelet transformation is deployed to deconstruct the waveform components. The delta encoding is further developed to decrease the magnitude. In conjunction with the Lempel-Ziv-Markov chain, the hybrid compression algorithm is implemented to achieve real-time compression for the synchro-waveform measurements. Moreover, an innovative error index that synergizes the time and frequency domain error and correlation is formulated to evaluate the waveform distortion. By integrating compression ratio, suitable parameters can be optimally selected. Finally, the simulation, laboratory experiments, as well as field tests across a spectrum of sampling frequencies and time intervals are conducted to substantiate the efficacy of the proposed method. Here, the outcomes demonstrated that a compression ratio of approximately 15.5 and 17.83 can be reached for 0.5 s and 1 s data under both offline and online scenarios, which equates to a substantial 93.5% to 94.39% reduction in data storage requirements.

High-fidelity synchro-waveform measurements↗

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗

A Model to Assess the Risk of Ice Accretion Due to Ice Crystal Ingestion in a Turbofan Engine and its Effects on Performance

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that were attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was one or more of the following anomalies: degraded engine performance, engine roll back, compressor surge and stall, and flameout of the combustor. The main focus of this research is the development of a computational tool that can estimate whether there is a risk of ice accretion by tracking key parameters through the compression system blade rows at all engine operating points within the flight trajectory. The tool has an engine system thermodynamic cycle code, coupled with a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Assumptions are made to predict the complex physics involved in engine icing. Specifically, the code does not directly estimate ice accretion and does not have models for particle breakup or erosion. Two key parameters have been suggested as conditions that must be met at the same location for ice accretion to occur: the local wet-bulb temperature to be near freezing or below and the local melt ratio must be above 10%. These parameters were deduced from analyzing laboratory icing test data and are the criteria used to predict the possibility of ice accretion within an engine including the specific blade row where it could occur. Once the possibility of accretion is determined from these parameters, the degree of blockage due to ice accretion on the local stator vane can be estimated from an empirical model of ice growth rate and time spent at that operating point in the flight trajectory. The computational tool can be used to assess specific turbine engines to their susceptibility to ice accretion in an ice crystal environment.

Jorgenson, Philip C. E.↗

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparison of laser models

Progress on the comparison of laser models is reported. Equations for an oscillatory model and a nonoscillatory model for the simulation of iodine laser operation are solved. Reaction rate coefficients used in both models are listed. Currently there are four models for the simulation of iodine laser operation are solved. Reaction rate coefficients used in both models are listed. Currently there are four models for the simulation of an iodine laser. They are: (1) a time dependent model; (2) a quasi-steady state model; (3) a noncompressible model; and (4) a compressible flow laser model. Current research is being directed toward: (1) parameter studies using the compressible flow laser model; (2) development of a two-pass amplifier model; and (3) solving a system of equations describing operation of the high powered iodine MOPA (master oscillator power amplifier).

Heinbockel, John H.↗

3D Printed Ceramic Reinforced Polymer Composites Microstructure and Mechanical Properties

In Fused Filament Fabrication (FFF) 3D printing a part is made by extruding material layer by layer. Benefits of FFF are the ability to print complex shapes quickly and at a lower cost compared to other manufacturing methods. In this work, filaments composed of either silicon carbide (SiC) or zirconium silicate ceramic particulates in a polylactic-acid (PLA) matrix were used to print specimens for microstructural analysis and mechanical testing. Pure PLA samples were also printed and tested as a baseline for comparison. A Design of Experiments approach was used to test the interactions between three different parameters and their effect on ultimate strength, Young’s modulus, and yield strength. For compression test specimens, these parameters were infill percentage, number of shells, and print orientation angle. For tensile test specimens, the parameters were layer height, number of shells, and infill orientation angle. Pre- and post-compression test samples were evaluated by scanning electron microscopy for microstructural analysis. Infill percentage had the greatest effect on mechanical properties while number of shells and print orientation angle had minor effects. When changing the layer lines from perpendicular to parallel, relative to the loading direction, SiC-PLA had higher mechanical properties while pure PLA properties had decreased, and zirconium silicate-PLA had mix results.

Fused filament fabrication↗

On the redistribution of charge in La 0.7 Sr 0.3 CrO 3 /La 0.7 Sr 0.3 MnO 3 multilayer thin films

The atomic and electronic structures of La 0.7 Sr 0.3 MnO 3 (LSMO)/La 0.7 Sr 0.3 CrO 3 (LSCO) multilayer thin films are investigated using aberration corrected scanning transmission electron microscopy (STEM) imaging and spectroscopy. Atomic resolution high angle annular dark-field reveals that LSMO layers have an expanded out-of-plane lattice parameter compared to compressed LSCO layers, contrasting with x-ray diffraction measurements. The expansion is found to result from preferential oxygen vacancy formation in LSMO during STEM sample preparation as determined by electron energy-loss spectroscopy. The La/Sr atom column intensity is also found to oscillate by about 4% between the LSMO and LSCO layers, indicative of La/Sr concentration variation. Using energy-dispersive x-ray spectroscopy in combination with image simulations, we confirm the La/Sr inhomogeneity and elucidate the origin of charge redistribution within the multilayer. These results illuminate the sensitivity of the technique to subtle structural, chemical, and electronic features that can arise to compensate charge imbalances in complex oxide heterostructures.

36 MATERIALS SCIENCE↗

An analytic and complete equation of state for condensed phase materials

Analytic equations of state (EOS) are intended to reproduce theoretical and experimental data in a single phase portion of the thermodynamic space. We devise a complete and thermodynamically consistent model with four distinct features: (1) a reference isotherm that remains thermodynamically stable, (2) a flexible specific heat model based on a fourth-order rational polynomial, (3) a Grüneisen parameter that depends on specific volume and temperature, and (4) pressure and internal energy functions that can be inverted analytically in temperature. The model aims to improve the accuracy of existing equations of state while remaining computationally efficient. To demonstrate its features, we include calibrations for single-crystal pentaerythritol tetranitrate (PETN), liquid nitromethane (NM), and hexagonal close-packed beryllium (Be) metal. The parameter optimization uses the specific heat capacity, Grüneisen parameter, and static compression curves obtained from density functional theory for the crystalline solids and molecular dynamics simulations for liquid NM. We also present a velocity autocorrelation function that yields accurate phonon densities of states for the EOS calibration from the molecular dynamics trajectories. Each of the three calibrations is constrained to enforce the ambient state from experimental measurements and validated against experimental Hugoniot data from multiple sources. We also include one-dimensional hydrodynamic simulations of the isentropic compression experiments for beryllium conducted at the Z facility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Examining the possibility that normal nuclear matter is quarkyonic

The possibility that nuclear matter might be quarkyonic is considered. Quarkyonic matter is high baryon density matter that is confined but can be approximately thought of as a filled Fermi sea of quarks surrounded by a shell of nucleons. Here, nuclear matter is described by the IdylliQ sigma model for quarkyonic matter, generalizing the noninteracting IdylliQ model [Y. Fujimoto et al., Phys. Rev. Lett. 132, 112701 (2024)] to include interactions with a σ meson and a pion. When such interactions are included, we find that isospin-symmetric nuclear matter binds with acceptable values of the compressibility and other parameters for nuclear matter at saturation. The energy per nucleon and sound velocity of such matter is computed, and the isospin dependence is determined. Nuclear matter is formed at a density close to but slightly above the density at which quarkyonic matter forms. Quarkyonic matter predicts a strong depletion of nucleons in normal nuclear matter at low momentum. Finally, such a depletion for nucleon momenta k ≲ 120 MeV is shown to be consistent with electron scattering data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Detection of Synchrophasor False Data Injection Attack using Feature Interactive Network

The synchrophasor data recorded by Phasor Measurement Units (PMUs) plays an increasingly critical role in the regulation and situational awareness of power systems. However, the widely installed PMUs are vulnerable to multiple malicious attacks from cyber hackers during data transmission and storage. To address this problem, a Modified Ensemble Empirical Mode Decomposition (MEEMD) is proposed first to extract the intrinsic mode functions of each Synchrophasor Data Attacks (SDA). The frequency-based adaptive screening criterion embedded in MEEMD is used to eliminate the false intrinsic mode functions. Next, a Multivariate Convolutional Neural Network (MCNN) is proposed to identify multiple SDA by utilizing the extracted intrinsic mode functions and original SDA as input vectors. A fusion block as the main structure of MCNN is also leveraged to increase the diversity of features and compress the model parameters. Integrating MEEMD and MCNN, a framework with automatic feature extraction and multi-source information fusion capability, referred to as Feature Interactive Network (FIN), is proposed to detect multiple SDA. Based on the proposed FIN framework, six types of SDA are explored for the first time using actual synchrophasor data in FNET/Grideye that was collected from different locations in the U.S. Eastern Interconnection. Finally, a large quantity of experiments with different attack strengths are used to evaluate the adaptability and classification performance of the proposed FIN.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Apollo soil mechanics experiment S-200

The physical and mechanical properties of the unconsolidated lunar surface material samples that were obtained during the Apollo missions were studied. Sources of data useful for deduction of soil information, and methods used to obtained the data are indicated. A model for lunar soil behavior is described which considers soil characteristics, density and porosity, strength, compressibility, and trafficability parameters. Lunar history and processes are considered, and a comparison is made of lunar and terrestrial soil behavior. The impact of the findings on future exploration and development of the moon are discussed, and publications resulting from lunar research by the soil mechanics team members are listed.

Mitchell, J. K.↗

Impact resistance and interlaminar fracture toughness of through-the-thickness reinforced graphite/epoxy

Five through-the-thickness stitch configurations are analyzed to determine the effect of impact resistance and interlaminar fracture toughness on T3000/3501-6 graphite/epoxy. The test specimens were stitched with either polyester or Kevlar yarns and with various stitch parameters. Tension and compression mechanical, impact and compression-after-impact, and double cantilever beam tests were conducted. It is observed that the stitched laminates have tension and compression strengths 20-25 percent lower than the strengths of unstitched laminates, the tension strength of stitched laminates is reduced with increasing number of stitches, and the compression strength increases as the number of stitches are increased. The impact data reveal that the Kevlar stitched laminates have less damage than unstitched laminates; the most effective configuration for suppressing impact damage and improving interlaminar fracture toughness consists of Kevlar yarns 1/4 inch apart with eight stitches per inch. The mode 1 critical strain energy release rate for the 1/4 inch Kevlar eight stitch laminate was calculated as 30 times higher than that of the unstitched.

Dexter, H. B.↗

A structural-stochastic model for the analysis and synthesis of cloud images

A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.

Garand, L.↗

Automatic commanding of the Mars Observer Camera

Mars Observer, launched in September 1992, was intended to be a 'survey-type' mission that acquired global coverage of Mars from a low, circular, near-polar orbit during an entire Martian year. As such, most of its instruments had fixed data rates, wide fields of view, and relatively low resolution, with fairly limited requirements for commanding. An exception is the Mars Observer Camera, or MOC. The MOC consists of a two-color Wide Angle (WA) system that can acquire both global images at low resolution (7.5 km/pixel) and regional images at commandable resolutions up to 250 m/pixel. Complementing the WA is the Narrow Angle (NA) system, that can acquire images at 8 resolutions from 12 m/pixel to 1.5 m/pixel, with a maximum crosstrack dimension of 3 km. The MOC also provides various forms of data compression (both lossless and lossy), and is designed to work at data rates from 700 bits per second (bps) to over 80k bps. Because of this flexibility, developing MOC command sequences is much more difficult than the routine mode-changing that characterizes other instrument operations. Although the MOC cannot be pointed (the spacecraft is fixed nadir-pointing and has no scan platform), the timing, downlink stream allocation, compression type and parameters, and image dimensions of each image must be commanded from the ground, subject to the constraints inherent in the MOC and the spacecraft. To minimize the need for a large operations staff, the entire command generation process has been automated within the MOC Ground Data System. Following the loss of the Mars Observer spacecraft in August 1993, NASA intends to launch a new spacecraft, Mars Global Surveyor (MGS), in late 1996. This spacecraft will carry the MOC flight spare (MOC 2). The MOC 2 operations plan will be largely identical to that developed for MOC, and all of the algorithms described here are applicable to it.

Caplinger, Michael↗

Recovery of Natural Gas Equipment Emissions into Gas Compression Engines for the Reduction of Potential Greenhouse Gas Emissions

Since the turn of the millennium, the United States (U.S.) oil and natural gas (ONG) industry has nearly doubled its natural gas production rate. As a result, the ONG industry has recently come under increasing scrutiny for its contributions to greenhouse gas (GHG) emissions. Consequently, various solutions to this problem have been proposed and formulated to reduce the impacts of GHG emissions on the environment. West Virginia University (WVU) have found it important to research the impacts of recovering vented gas streams into prime-mover engines. The U.S. Department of Energy (DOE) and National Energy Technology Laboratory (NETL) have granted WVU funding to research and develop a “Methane Mitigator” (M2) - a “Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry.” One of the main areas of interest for this research was the collection of emissions from natural gas equipment into a Caterpillar G3508J natural gas compression engine. The parameters being analyzed from the engine were brake-specific emissions and power output. The emissions sources considered for this research were pneumatic controllers (PCs), reciprocating compressor vents, and the engine’s open crankcase breather. The compressor vent and PC emissions were simulated using a mass flow controller (MFC) and flowed into the engine using two separate methods: (1) directly into the air intake, and (2) through a retrofitted closed crankcase ventilation system (CCV), serving as a buffer volume. The crankcase emissions were quantified without the CCV, and the impact on exhaust emissions from circulating the crankcase gases into the intake was measured. The simulated compressor vent and PC flows from the MFC had limited effect on the steady state operation of the engine and resulting performance. When the simulated flows were fed directly into the engine’s air intake, the changes within the engine’s continuous performance and emission parameters were larger but lasted for shorter durations. Conversely, when the simulated flows were fed into the CCV before entering the air intake, the changes in the engine’s performance and emission parameters were less pronounced for continuous analysis but lasted for longer durations. In either case, the continuous emission changes in both emissions and performance varied in size depending on the test scenario being run, but the cycle average changes in emissions and performance showed little impact overall compared to the engine’s baseline operation. As a result, the inclusion of a CCV shows a decrease in baseline carbon dioxide equivalent (CO2-eq.) engine emissions (from combined exhaust and open crankcase) of almost 4%. Likewise, the CCV inclusion reduced baseline total methane (CH4) from combined exhaust and open crankcase by upwards of 16%. These atmospheric emissions only decreased further with the inclusions of collected PC and compressor vent flows. The resulting changes in time-averaged rated exhaust behavior (or lack thereof) prove that the proposed M2 system could likely be deployed at sites with modern lean-burn natural gas engines as a viable option for reducing and eliminating potential GHG sources that would have otherwise been unutilized as energy sources.

03 NATURAL GAS↗