Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Characteristic Curves”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Surface fluctuating hydrodynamics methods for the drift-diffusion dynamics of particles and microstructures within curved fluid interfaces

Here we introduce fluctuating hydrodynamics approaches on surfaces for capturing the drift-diffusion dynamics of particles and microstructures immersed within curved fluid interfaces of spherical shape. We take into account the interfacial hydrodynamic coupling, traction coupling with the surrounding bulk fluid, and thermal fluctuations. For fluid-structure interactions, we introduce Immersed Boundary Methods (IBM) and related Stochastic Eulerian-Lagrangian Methods (SELM) for curved surfaces. We use these approaches to investigate the statistics of surface fluctuating hydrodynamics and microstructures. For velocity autocorrelations, we find characteristic power-law scalings $τ^{-1}, τ^{-2}$, and plateaus can emerge. This depends on the physical regime associated with the geometry, surface viscosity, and bulk viscosity. This differs from the characteristic $τ^{-3/2}$ scaling for bulk three dimensional fluids. We develop theory explaining these observed power-laws associated with time-scales for dissipation within the fluid interface and coupling to the surrounding fluid. We then use our introduced methods to investigate a few example systems and roles of hydrodynamic coupling and thermal fluctuations including for the kinetics of passive particles and active microswimmers in curved fluid interfaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Synthesis and characterization of amorphous Fe2.75Dy-oxide thin films demonstrating room-temperature semiconductor, magnetism, and optical transparency

Recently, amorphous/disordered oxide thin films made from Fe and lanthanides like Dy and Tb have been reported to have a rich set of magnetic, optical, and electronic properties, as well as room-temperature magneto-electric coupling with multiferroics [A. Malasi et al., Sci. Rep. 5, 18157 (2015); H. Taz et al., Sci. Rep. 6, 27869 (2016); and H. Taz et al., Sci. Rep. 10, 1–10 (2020)]. Here, we report the synthesis and detailed characterization of Fe2.75Dy-oxide thin films prepared on various substrates using electron beam co-evaporation. The structure, chemistry, electric, magnetic, and optical properties were studied for the as-prepared and annealed (373 K, in air, 1 h) films of thickness 40 nm. High resolution transmission electron microscopy and electron diffraction study showed that the films were amorphous in both the as-prepared and annealed states. The electron energy-loss spectroscopy studies quantified that metal oxygen stoichiometry changed from Fe2.75Dy-O1.5 to Fe2.75Dy-O1.7 upon annealing. Synchrotron-based x-ray absorption spectroscopy investigation confirmed that the as-prepared films were highly disordered with predominantly metallic Fe and Dy states that became slightly oxidized with annealing in air. The as-prepared amorphous films demonstrated significantly high value of ordinary (∼10 cm2/V s) and anomalous (∼102 cm2/V s) Hall mobility and high electrical conductivity of ∼103 S/cm at room temperature. The cryogenic magnetic property measurement shows two-step magnetization below 200 K, suggesting exchange-spring magnetic interaction. The nature of the field cooled and zero-field cooled curves suggested a spin-glass like transition between 78 K and 80 K, with a characteristic broad peak. The Tauc plot analysis from optical transmission spectra confirms the existence of an optical bandgap of ∼2.42 eV that increased slightly to ∼2.48 eV upon annealing. This rich set of transport, optical, and magnetic properties in these thin films is very exciting and points to potential applicability in low-cost multifunctional devices requiring a combination of transparent, semiconducting, and magnetic responses, such as in spintronics.

Prasad Koirala, Krishna (ORCID:000000029137917X)↗
DOE OSTI2020

Non-invasive measurement of leaf water content and pressure–volume curves using terahertz radiation

In this paper we describe a non-invasive method of measuring leaf water content using THz radiation and combine this with psychrometry for determination of leaf pressure–volume relationships. In contrast to prior investigations using THz radiation to measure plant water status, the reported method exploits the differential absorption characteristic of THz radiation at multiple frequencies within plant leaves to determine absolute water content in real-time. By combining the THz system with a psychrometer, pressure–volume curves were generated in a completely automated fashion for the determination of leaf tissue water relations parameters including water potential at turgor loss, osmotic potential at full turgor and the relative water content at the turgor loss point. This novel methodology provides for repeated, non-destructive measurement of leaf water content and greatly increased efficiency in generation of leaf PV curves by reducing user handling time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Characterizing Uncertainty in Synthetic Tropical Cyclone Hazard Models for U.S. Energy Infrastructure Resilience

Tropical Cyclones (TCs) are intense storms that pose a persistent and considerable risk to coastal communities and infrastructure in the global tropics and subtropics, including the United States (US). With known limitations associated with observations and high-resolution earth system models, synthetic TC models that capture a wide spectrum of storm possibilities have been developed to robustly quantify TC risk. Here we examine the simulation of various TC features in the North Atlantic relevant for US coastal risk in three synthetic TC models forced with ERA5 reanalysis: MIT, CHAZ and RAFT. While there is a broad agreement among these models in terms of their representation of salient TC characteristics, certain differences do exist. To connect these modeling uncertainties with energy infrastructure resilience, we apply fragility curves that link simulated TC intensities to damage probabilities, demonstrating how uncertainty in storm states may translate into that in coastal impacts. Our study indicates that acknowledging and accounting for inter-model uncertainty leads to more reliable risk assessments, strengthening science-to-action pathways for managing risks associated with TCs.

Baby John, Effy↗
DOE OSTI2024

Experimental Operation of a Prototype 750C Advanced Chloride Molten Salt Bellows Valve

To achieve DOE 2030 SunShot targets that reduce the cost of liquid-based solar by an additional 40% to 70% beyond 2018 costs, a more reliable, highly manufacturable flow valve, capable of achieving operational temperatures of >700°C is required [1]. This paper investigates the development of an innovative high-temperature chloride molten salt valve, with operation up to 750°C. This valve is intended to be employed within Gen 3 CSP liquid-based thermal energy storage (TES) systems as well as Gen 4 modular salt reactor (MSR) technologies. This work details the general design and flow testing of a bellows-seal flow control valve (FCV). This design includes an integrated closed-loop thermal control system to ensure robust design for freeze-thaw cycles. The self-contained thermal management STM system, is unique in the salt valve industry since it is an integrated solution to provide a consistent, repeatable alternative to typical heat tracing. Additionally, the design includes the employment of a novel heat pipe valve stem to facilitate enhanced passive thermal management into the valve assembly. This valve stem heat pipe is designed to facilitate natural circulation within the bonnet to ensure robust operation, during both nominal and transient thermal operation. The valve body and trim will be designed using SS316H, consistent with Flowserve Corporation’s existing product base and is code qualified but will utilize clad material for materials corrosion, manufacturing cost reduction and compatibility to ensure design flexibility. A test campaign was performed in this investigation utilizing a novel 750°C ternary chloride (20%NaCl/40%MgCl2/40%KCl by mol. wt. %) molten salt flow loop. A discussion about the design and installation of the valves within this test bed is provided for this investigation. Valve test results from this study assessed Cv curves as well as multiple actuator cycles, under varying thermodynamic and operational mode conditions, which would be characteristic within a commercial molten salt facility. The results indicate nominal operation for the baseline design, though improved performance and reliability is expected with the full designed FCV.

Armijo, Kenneth (ORCID:0000000346832147)↗
DOE OSTI2020

Synthetic residential load models for smart city energy management simulations

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterize the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

​​Hydrogen Transportation and Distributed Energy Systems Seismic Risk Assessment for Cascadia Subduction Zone Airport Facilities​

Portland International Airport in Oregon is exploring operating a fleet of 28 fuel cell electric buses to support airport operations and possibly provide backup power during outages. In this report, we evaluate the risk of hydrogen deployment at an airport considering the potential for seismic activity. We present a seismic risk assessment for pressurized piping for a generic hydrogen refueling station at the airport. Only pressurized piping was considered in the risk analysis because of its vulnerability and availability of fragility information unlike the other components. Seismic capacity of other components should be included as more information becomes available. To characterize the seismic hazard, we considered the initiating event frequency of a Cascadia Subduction Zone earthquake event based on data from the literature. Seismic stressors that translate to the site from an earthquake event are expressed as peak ground acceleration. Site disturbance is characterized as a function of soil conditions, represented by different shear wave velocity values, which affect how seismic waves propagate and impact structures. Pipe fragility curves as a function of seismic capacity were used to correlate ground acceleration and failure probability. These fragility characteristics were combined with site-specific soil conditions to calculate the probability of pipe rupture during a seismic event. It should be noted that multiple simultaneous failures due to an earthquake event as a common cause are not considered. Some epistemic uncertainties such as self-exciting shocks, aftershocks, and the time variant nature of the ground motion are not considered either.

08 HYDROGEN↗
DOE OSTI2026

Third-body stabilization of supercritical CO 2 in CO oxidation: development and application of a ReaxFF force field for the CO/O/CO 2 system

Supercritical CO 2 (scCO 2 ) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO 2 matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. Here, to address this issue, we have developed a novel ReaxFF reactive force field for the CO 2 /CO/O system. The force field parameters were calibrated using density functional theory and second-order Møller-Plesset calculations to model CO 2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO 2 crystal, the pressure characteristics of bulk scCO 2 , the equation-of-state behavior over a wide pressure–density range, the pressure dependence of the C–O bond length under compression, and the structural properties of liquid and scCO 2 , as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O → CO 2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO 2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO 2 environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 ± 3.6 kcal/mol over 112.4 ± 17.9 ps. Kinetic energy decomposition reveals that ∼ 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom. This ReaxFF force field establishes a mechanistic foundation for third-body stabilization in dense reactive environments.

Chowdhury, Emdadul Haque [Pennsylvania State Univ.↗
DOE OSTI2019

Transmission Expansion Planning Test System for AC/DC Hybrid Grid With High Variable Renewable Energy Penetration

Test systems are important tools and benchmark for power system research. Currently, there is a lack of standard test systems for modern transmission expansion planning (TEP) research, especially under high variable renewable energy (VRE) penetrations. This article describes a 38-bus test system named the HRP-38 system dedicated to TEP. “HRP” stands for high renewable penetration. The objective of establishing such a system is to provide a consistent platform for different TEP methods to be tested and compared. The test system considers high VRE penetration of more than 30% energy share, which will be an important feature in many power systems in the future. Both AC and DC candidate lines are given to provide sufficient transmission planning alternatives. The complexity of the test system is well balanced considering calculation tractability and the ability to test the performance of the TEP planning model. The network topology, generation mix and load characteristics are described in detail. Year-round time series of VRE (wind power and PV) output and load curves for each bus are provided to facilitate a detailed evaluation of the transmission grid configuration under high VRE penetration. Finally, four benchmark results with different optimization settings are provided for the HRP-38 system.

AC/DC hybrid↗
DOE OSTI2026

Multi-Split Variable Refrigerant Flow (VRF) System Building Energy Simulations Using Performance Maps

Multi-split variable refrigerant flow (VRF) systems are highly energy-efficient HVAC (heating, ventilation and air conditioning) technologies that connect a single outdoor unit to multiple independent indoor terminal units using a common refrigerant circuit and a variable-speed compressor. Building energy simulations that incorporate VRF systems help model their unique operational characteristics and predict energy consumption in specific building designs. Traditionally, EnergyPlus models these systems by employing multiple sets of performance curves to characterize both individual terminal units and the outdoor unit. However, producing these curves is labor intensive and error prone, and they often do not capture all the key input and output variables. This paper introduces a novel approach that uses multi-dimensional performance maps to model VRF systems in building environments for space cooling. In this approach, performance maps are developed at the component level—separately for the outdoor unit and for each indoor terminal. The new modeling method is validated within EnergyPlus via a Python plug-in that contains a simple solver loop to coordinate the component-level, indoor, and outdoor unit maps. Furthermore, because performance maps can span more variables than traditional performance curves, they offer the opportunity to implement advanced controls, such as enhanced dehumidification and compressor modulation. A VRF air conditioner’s hardware system was modeled using the DOE/ORNL Heat Pump Design Model, which was automated to produce extensive performance maps for both the indoor and outdoor units.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗
DOE OSTI2023

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗
DOE OSTI2021

The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.

Lian, Zhichuang↗
DOE OSTI2024

A Comprehensive Model for Analyzing the Effects of Power Outages on Customers

Power outages can cause significant inconveniences to critical services and substantial economic losses. Therefore, it is crucial to systematically analyze the impact on customers during power outages caused by various factors, such as severe thunderstorms, floods, vegetation, or mechanical problems, and to plan for reliable operation and control under such events. Power outages in different locations may exhibit varying characteristics regarding customer impact. In this paper, we present a mathematical model that captures the essential characteristics of customer impact during power outages. The parameters of our model include impact duration, recovery duration, maximum impact level, increase curve parameter, and decrease curve parameter. We demonstrate how historical power outage data can be fitted to our model, enabling a systematic comparison of outages caused by different factors in various locations.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗
DOE OSTI2022

Decay Curve Correction Analysis Report

The decay curve analysis that is done on the short-lived radionuclide gas samples is used to differentiate between gaseous radionuclides that have the same characteristic gamma decay energy, 511 kiloelectron-volts (keV). A sample of stack gas is isolated and the total counts in the 511 keV peak are counted repeatedly in 10-second intervals to evaluate the decay rate of the sample over time. Analysis of this decay data required a series of steps. First, a raw data report is generated by the gamma acquisition system, based on an analysis template within the acquisition software. The data report file was then loaded into Microsoft Word, and a macro was used to perform minor formatting (remove colons and insert tabs between data columns) to allow analysis within Excel. The file is then saved as a text file at this point. The text file is then uploaded into Excel and a series of macros are used to add labels, calculate radioactive decay constants, and analyze the gamma decay data using linear regression techniques. The analysis template has been used since 1998 for stack 53000303 (TA-53, building 0003, exhaust stack 03) and 2000 for stack 53000702. The overall process, including the gamma report format and the macros used in Word and Excel for processing the report, had remained unchanged until 2015. In October of 2015, staff made a change to the report template in the gamma acquisition software which resulted in an error in the calculations later performed by the Excel macro. This error was not caught until a more in-depth review of the analysis took place regarding 2020 data. This report covers a much more complete review of the issue that occurred regarding the decay curve analysis, a review of the calculations completed to correct the issue, a review of the updated decay curve analysis process, and recommendations for moving forward.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Caldera Infrastructure Charge Module (ICM)

Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as "Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2019

On the Origin of SN 2016hil—A Type II Supernova in the Remote Outskirts of an Elliptical Host

Type II supernovae (SNe) stem from the core collapse of massive ($>8\ M_{\odot}$) stars. Owing to their short lifespan, we expect a very low rate of such events in elliptical host galaxies, where the star-formation rate is low, and which mostly consist of an old stellar population. SN 2016hil (iPTF16hil) is a Type II supernova located in the extreme outskirts of an elliptical galaxy at redshift $z=0.0608$ (projected distance $27.2$ kpc). It was detected near peak brightness ($M_{r} \approx -17$ mag) 9 days after the last nondetection. SN 2016hil has some potentially peculiar properties: while presenting a characteristic spectrum, the event was unusually short lived and declined by $\sim 1.5$ mag in $< 40$ days, following an apparently double-peaked light curve. Its spectra suggest a low metallicity ($Z<0.4\ Z_{\odot}$). We place a tentative upper limit on the mass of a potential faint host at $\log(M/M_{\odot}) =7.27^{+0.43}_{-0.24}$ using deep Keck optical imaging. In light of this, we discuss the possibility of the progenitor forming locally, and other more exotic formation scenarios such as a merger or common-envelope evolution causing a time-delayed explosion. Further observations of the explosion site in the ultraviolet are needed in order to distinguish between the cases. Regardless of the origin of the transient, observing a population of such seemingly hostless Type II SNe could have many uses, including an estimate the number of faint galaxies in a given volume, and tests of the prediction of a time-delayed population of core-collapse SNe in locations otherwise unfavorable for the detection of such events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

VFA Biorefinery Design for Informed Production of Ground and Aviation Fuels

The rising demand for low-carbon intensity fuel options requires evaluation of a system which can support their production economically and sustainably. Volatile fatty acids (VFAs) ranging from C2 to C8 can be derived in high yield from arrested anaerobic digestion of biomass. This talk provides an overview of our work in which we upgrade wet waste-derived VFAs using ketonization to elongate their carbon backbone to reach a range relevant to jet or diesel fuels. Kinetic models were used to predict ketone profiles from varying VFA profiles, thereby informing potential carbon flow to either (a) mixed paraffins for use in diesel or aviation fuel, or (b) ethers for use in diesel fuel. To do this, the anticipated products were screened for critical fuel characteristics using predictive tools. The criteria for neat and blended bioblendstocks were chosen based on conventional petrofuel requirements, and they were applied to inform fuel targets, identify limiting characteristics, and guide conversion development. While paraffins can serve as either diesel or aviation fuels, the latter has stringent criteria which include a precise distillation curve range tied to carbon distribution. Fuels which fall outside this range typically fail to meet other property metrics, and as such flashpoint and viscosity were identified as potentially limiting properties of this VFA aviation fuel. However, paraffin fractions which fall outside aviation criteria may meet diesel fuel requirements, which are looser except for the flashpoint minimum. Flashpoint was also a concern for smaller VFA diesel ethers, which posed an additional oxygenate risk of high water solubility. This fuel-informed conversion design process was demonstrated through production of paraffins with reduced sooting as compared to petrodiesel (~34%), and increased renewable aviation fuel blend levels (>70%). VFA-derived ethers improved petrodiesel by increasing fuel autoignition quality by 56% and reducing sooting by 86%. These VFA aviation and diesel fuels could enable greenhouse gas (GHG) reductions of over 165% and 50%, respectively, relative to their purely fossil-derived counterparts. Collectively, this work provides (i) an overview of how we leveraged the flexibility of VFAs for fuel production; and (ii) insight into the potential of a VFA biorefinery to accommodate varied feed and fuel applications, while also considering the merit of tailored fuel production pathways and GHG reduction potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Resonant Frequency Derived from the Rayleigh-Wave Dispersion Image: The High-Impedance Boundary Problem

In this work, we present a simple and automated approach to estimate primary site-response resonance, layer thickness, and shear-wave velocity directly from a dispersion image for a layer over half-space problem. We demonstrate this for high-impedance boundary conditions that lie in the upper tens of meters. Our approach eliminates the need for time-consuming dispersion curve picking and 1D shear-wave velocity inversion for large data volumes that can capture velocity structure in profile. We highlight important relationships between dispersion characteristics and resonance parameters through synthetic modeling and field data acquired over Atlantic Coastal Plain sediments. In this environment, shallow soil conditions are critical to accurately estimate earthquake site response. We suggest that this image processing approach can be applied to a range of high-impedance conditions, at a range of scales, or can provide model constraints for more complex velocity structures.

58 GEOSCIENCES↗