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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Implementation of the Glued Sphere Discrete Element Model for Non-Spherical Particles in MFiX Software

To enhance solver capabilities, simulation flexibility and model validation within the MFiX software, the U.S. Department of Energy (DOE) is funding efforts to develop and integrate the glued-sphere discrete element method into the latest version of MFiX as a dedicated computational module. The glued-sphere discrete element method is a numerical technique to depict the behavior of non-spherical particles in granular flows or particulate systems by representing them as a collection of component spheres. These spheres are bonded together to approximate the shape and mechanical/chemical properties of a more complex particle. The method effectively reuses the existing sphere-sphere collision algorithm, interphase momentum and heat transfer calculations utilized in the traditional discrete element method, extending these capabilities to non-spherical particles. Additionally, this method explicitly resolves intra-particle temperature and species distributions. The MFiX glued-sphere computational module includes tools for generating glued sphere configurations, a dedicated solver, and visualization capabilities in post-processing. More specifically within the computational module, collision detection and calculations were first performed on component spheres and then mapped onto non-spherical particles. The linear spring-dashpot model was utilized to simulate the sphere-sphere interactions.

Ke, Renjie↗
DOE OSTI2015

Accuracy of Routine Treatment Planning 4-Dimensional and Deep-Inspiration Breath-Hold Computed Tomography Delineation of the Left Anterior Descending Artery in Radiation Therapy

Purpose: To assess the feasibility of radiation therapy treatment planning 4-dimensional computed tomography (4DCT) and deep-inspiration breath-hold (DIBH) CT to accurately contour the left anterior descending artery (LAD), a primary indicator of radiation-induced cardiac toxicity for patients undergoing radiation therapy. Methods and Materials: Ten subjects were prospectively imaged with a cardiac-gated MRI protocol to determine cardiac motion effects, including the displacement of a region of interest comprising the LAD. A series of planar views were obtained and resampled to create a 3-dimensional (3D) volume. A 3D optical flow deformable image registration algorithm determined tissue displacement during the cardiac cycle. The measured motion was then used as a spatial boundary to characterize motion blurring of the radiologist-delineated LAD structure for a cohort of 10 consecutive patients enrolled prospectively on a breast study including 4DCT and DIBH scans. Coronary motion–induced blurring artifacts were quantified by applying an unsharp filter to accentuate the LAD structure despite the presence of motion blurring. The 4DCT maximum inhalation and exhalation respiratory phases were coregistered to determine the LAD displacement during tidal respiration, as visualized in 4DCT. Results: The average 90th percentile heart motion for the region of interest was 0.7 ± 0.1 mm (left–right [LR]), 1.3 ± 0.6 mm (superior–inferior [SI]), and 0.6 ± 0.2 mm (anterior–posterior [AP]) in the cardiac-gated MRI cohort. The average relative increase in the number of voxels comprising the LAD contour was 69.4% ± 4.5% for the DIBH. The LAD volume overestimation had the dosimetric impact of decreasing the reported mean LAD dose by 23% ± 9% on average in the DIBH. During tidal respiration the average relative LAD contour increase was 69.3% ± 5.9% and 67.9% ± 4.6% for inhalation and exhalation respiratory phases, respectively. The average 90th percentile LAD motion was 4.8 ± 1.1 mm (LR), 0.9 ± 0.4 mm (SI), and 1.9 ± 0.6 mm (AP) for the 4DCT cohort, in the absence of cardiac gating. Conclusions: An anisotropic margin of 2.7 mm (LR), 4.1 mm (SI), and 2.4 mm (AP) was quantitatively determined to account for motion blurring and patient setup error while placing minimum constraint on the plan optimization.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

In-stream hydrokinetic power: Review and appraisal

The objective of this paper is to provide a review of in-stream hydrokinetic power, which is defined as electric power generated by devices capturing the energy of naturally flowing water-stream, tidal, or open ocean flows-without impounding the water. North America has significant in-stream energy resources, and hydrokinetic electric power technologies to harness those resources have the potential to make a significant contribution to U.S. electricity needs by adding as much as 120 TWh/year from rivers alone to the present hydroelectric power generation capacity. Additionally, tidal and ocean current resources in the U.S. respectively contain 438 TWh/year and 163 TWh/year of extractable power. Among their attractive features, in-stream hydrokinetic operations do not contribute to greenhouse gas emissions or other air pollution and have less visual impact than wind turbines. Since these systems do no utilize dams the way traditional hydropower systems typically do, their impact on the environment will differ, and a small but growing number of studies support conclusions regarding those impacts. Furthermore, potential environmental impacts include altered water quality, altered sediment deposition, altered habitats, direct impact on biota, and navigability of waterways.

13 HYDRO ENERGY↗
DOE OSTI2023

Data-Driven Transition Path Analysis Yields a Statistical Understanding of Sudden Stratospheric Warming Events in an Idealized Model

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

Computer-aided diagnosis for classifying benign versus malignant thyroid nodules based on ultrasound images: A comparison with radiologist-based assessments

Purpose: To develop a semiautomated computer-aided diagnosis (CAD) system for thyroid cancer using two-dimensional ultrasound images that can be used to yield a second opinion in the clinic to differentiate malignant and benign lesions. Methods: A total of 118 ultrasound images that included axial and longitudinal images from patients with biopsy-confirmed malignant (n = 30) and benign (n = 29) nodules were collected. Thyroid CAD software was developed to extract quantitative features from these images based on thyroid nodule segmentation in which adaptive diffusion flow for active contours was used. Various features, including histogram, intensity differences, elliptical fit, gray-level co-occurrence matrixes, and gray-level run-length matrixes, were evaluated for each region imaged. Based on these imaging features, a support vector machine (SVM) classifier was used to differentiate benign and malignant nodules. Leave-one-out cross-validation with sequential forward feature selection was performed to evaluate the overall accuracy of this method. Additionally, analyses with contingency tables and receiver operating characteristic (ROC) curves were performed to compare the performance of CAD with visual inspection by expert radiologists based on established gold standards. Results: Most univariate features for this proposed CAD system attained accuracies that ranged from 78.0% to 83.1%. When optimal SVM parameters that were established using a grid search method with features that radiologists use for visual inspection were employed, the authors could attain rates of accuracy that ranged from 72.9% to 84.7%. Using leave-one-out cross-validation results in a multivariate analysis of various features, the highest accuracy achieved using the proposed CAD system was 98.3%, whereas visual inspection by radiologists reached 94.9% accuracy. To obtain the highest accuracies, “axial ratio” and “max probability” in axial images were most frequently included in the optimal feature sets for the authors’ proposed CAD system, while “shape” and “calcification” in longitudinal images were most frequently included in the optimal feature sets for visual inspection by radiologists. The computed areas under curves in the ROC analysis were 0.986 and 0.979 for the proposed CAD system and visual inspection by radiologists, respectively; no significant difference was detected between these groups. Conclusions: The use of thyroid CAD to differentiate malignant from benign lesions shows accuracy similar to that obtained via visual inspection by radiologists. Thyroid CAD might be considered a viable way to generate a second opinion for radiologists in clinical practice.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Analysis and visualization of energy densities. I. Insights from real-time time-dependent density functional theory simulations

In this article, we report a scheme to analyze and visualize the energy density fluctuations during the real-time time-dependent density functional theory (RT-TDDFT) simulations. Using Ag 4 –N 2 complexes as examples, here we show that the grid-based Kohn–Sham energy density can be computed at each time step using a procedure from Nakai and coworkers. Then the instantaneous energy of each molecular fragment (such as Ag 4 and N 2 ) can be obtained by partitioning the Kohn–Sham energy densities using Becke or fragment-based Hirshfeld (FBH) scheme. A strong orientation-dependence is observed for the energy flow between the Ag 4 cluster and a nearby N 2 molecule in the RT-TDDFT simulations. Future applications of such an energy density analysis in electron dynamics simulations are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

TH-A-18A-01: Innovation in Clinical Breast Imaging

Several novel modalities have been or are on the verge of being introduced into the breast imaging clinic. These include tomosynthesis imaging, dedicated breast CT, contrast-enhanced digital mammography, and automated breast ultrasound, all of which are covered in this course. Tomosynthesis and dedicated breast CT address the problem of tissue superimposition that limits mammography screening performance, by improved or full resolution of the 3D breast morphology. Contrast-enhanced digital mammography provides functional information that allows for visualization of tumor angiogenesis. 3D breast ultrasound has high sensitivity for tumor detection in dense breasts, but the imaging exam was traditionally performed by radiologists. In automated breast ultrasound, the scan is performed in an automated fashion, making for a more practical imaging tool, that is now used as an adjunct to digital mammography in breast cancer screening. This course will provide medical physicists with an in-depth understanding of the imaging physics of each of these four novel imaging techniques, as well as the rationale and implementation of QC procedures. Further, basic clinical applications and work flow issues will be discussed. Learning Objectives: To be able to describe the underlying physical and physiological principles of each imaging technique, and to understand the corresponding imaging acquisition process. To be able to describe the critical system components and their performance requirements. To understand the rationale and implementation of quality control procedures, as well as regulatory requirements for systems with FDA approval. To learn about clinical applications and understand risks and benefits/strength and weakness of each modality in terms of clinical breast imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Protection heater design validation for the LARP magnets using thermal imaging

Protection heaters are essential elements of a quench protection scheme for high-field accelerator magnets. Various heater designs fabricated by LARP and CERN have been already tested in the LARP high-field quadrupole HQ and presently being built into the coils of the high-field quadrupole MQXF. In order to compare the heat flow characteristics and thermal diffusion timescales of different heater designs, we powered heaters of two different geometries in ambient conditions and imaged the resulting thermal distributions using a high-sensitivity thermal video camera. We observed a peculiar spatial periodicity in the temperature distribution maps potentially linked to the structure of the underlying cable. Two-dimensional numerical simulation of heat diffusion and spatial heat distribution have been conducted, and the results of simulation and experiment have been compared. Imaging revealed hot spots due to a current concentration around high curvature points of heater strip of varying cross sections and visualized thermal effects of various interlayer structural defects. Furthermore, thermal imaging can become a future quality control tool for the MQXF coil heaters.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Dimensionality effects on multicomponent ionic transport and surface complexation in porous media

Coulombic interactions between charged species in pore water and at surface/solution interfaces are of pivotal importance for multicomponent reactive transport in porous media. In this study, we investigate the impact of domain dimensionality on electrostatically coupled dispersion and surface-solution reactions during transport of acidic plumes and major ions in porous media. Column and quasi two-dimensional flow-through experiments were performed, with identical silica porous media and under the same advection-dominated conditions. Equal mass fluxes of different electrolyte solutions (i.e., HCl - pH ~ 2.8, NaBr - 100 mM, HCl - pH ~ 2.8 plus NaBr - 100 mM) were continuously injected in the 1-D and 2-D experiments and breakthrough curves of pH and major ions were measured at the outlet of the domains. The presence of pronounced ionic strength gradients in the transverse direction in the 2-D setup caused distinct retardation and transport behaviors of protons and major ions which were not observed in the one-dimensional column experiments. Furthermore, in the cases of salt electrolytes injection, considerably enhanced release of H + (>61%) from the quartz surface was observed in the multidimensional system compared to the one-dimensional setup. Reactive transport modeling was performed to reproduce the experimental outcomes and to analyse the coupling between transport processes, based on the Nernst-Planck formulation of diffusive/dispersive fluxes and on surface complexation reactions at the solid-solution interface. Electrostatic interactions between Na + , B – , and H + , and deprotonation of the quartz surface upon the formation of sodium outer-sphere complexes, are the primary controllers of the spatial and temporal features displayed by the pH and major ions measurements. The reactive transport simulations allowed us to interpret the experimental observations, to visualize the distribution and spatio-temporal evolution of dissolved and solid species, to identify a spatially heterogeneous zonation of Coulombic interactions with distinct behavior at the fringe and core of the injected plumes in the multidimensional setup, and to quantify the different components of the Nerst-Planck fluxes of the charged solutes. This study demonstrates that the domain dimensionality directly affects electrostatic interactions between charged aqueous species in the pore water and surface complexation reactions at the solid-solution interface. The non-trivial effects of dimensionality on multicomponent ionic transport result in a significantly different behavior in 1-D and 2-D systems.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea

Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn- and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO 2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn-eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.

58 GEOSCIENCES↗
DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Tabulated Database of Closed-Loop Geothermal Systems Performance for Cloud-Based Technical and Economic Modeling of Heat Production and Electricity Generation: Preprint

To better understand the heat production, electricity generation performance and economic viability of closed loop geothermal systems in hot-dry-rock, the Closed Loop Geothermal Group, a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and super-critical CO2) while varying seven continuous independent parameters of interest (i.e., mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an Organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the TEA (techno-economic analysis) script are provided.

co-axial↗
DOE OSTI2014

Software-Based Challenges of Developing the Future Distribution Grid

The software that the utility industry currently uses may be insufficient to analyze the distribution grid as it rapidly modernizes to include active resources such as distributed generation, switch and voltage control, automation, and increasingly complex loads. Although planners and operators have traditionally viewed the distribution grid as a passive load, utilities and consultants increasingly need enhanced analysis that incorporates active distribution grid loads in order to ensure grid reliability. Numerous commercial and open-source tools are available for analyzing distribution grid systems. These tools vary in complexity from providing basic load-flow and capacity analysis under steady-state conditions to time-series analysis and even geographical representations of dynamic and transient events. The need for each type of analysis is not well understood in the industry, nor are the reasons that distribution analysis requires different techniques and tools both from those now available and from those used for transmission analysis. In addition, there is limited understanding of basic capability of the tools and how they should be practically applied to the evolving distribution system. The study reviews the features and state of the art capability of current tools, including usability and visualization, basic analysis functionality, advanced analysis including inverters, and renewable generation and load modeling. We also discuss the need for each type of distribution grid system analysis. In addition to reviewing basic functionality current models, we discuss dynamics and transient simulation in detail and draw conclusions about existing software?s ability to address the needs of the future distribution grid as well as the barriers to modernization of the distribution grid that are posed by the current state of software and model development. Among our conclusions are that accuracy, data transfer, and data processing abilities are key to future distribution grid modeling, and measured data sources are a key missing element . Modeling tools need to be calibrated based on measured grid data to validate their output in varied conditions such as high renewables penetration and rapidly changing topology. In addition, establishing a standardized data modeling format would enable users to transfer data among tools to take advantage of different analysis features. ?

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Carcass appearance does not influence scavenger avoidance of carnivore carrion

Abstract The selection or avoidance of certain carrion resources by vertebrate scavengers can alter the flow of nutrients in ecosystems. Evidence suggests higher trophic level carrion is scavenged by fewer vertebrate species and persists longer when compared to lower trophic level carrion, although it is unclear how scavengers distinguish between carcasses of varying species. To investigate carnivore carrion avoidance and explore sensory recognition mechanisms in scavenging species, we investigated scavenger use of intact and altered (i.e., skin, head, and feet removed) coyote— Canis latrans (carnivore) and wild pig— Sus scrofa (omnivore) carcasses experimentally placed at the Savannah River Site, SC, USA. We predicted carnivore carcasses would persist longer due to conspecific and intraguild scavenger avoidance. Further, we hypothesized visually modifying carcasses would not reduce avoidance of carnivore carrion, given scavengers likely depend largely on chemical cues when assessing carrion resources. As expected, mammalian carnivores largely avoided scavenging on coyote carcasses, resulting in carnivore carcasses having longer depletion times than wild pig carcasses at intact and altered trials. Therefore, nutrients derived from carnivore carcasses are not as readily incorporated into higher trophic levels and scavengers largely depend on olfactory cues when assessing benefits and risks associated with varying carrion resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Dataset for scientific paper "Simulated plant‑mediated oxygen input has strong impacts on fine‑scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands", a modeling study based on field observation at the tidal salt marshes of the Parker River Estuary, Massachusetts, United States

This dataset is the raw and processed data for the paper "Simulated plant ‑ mediated oxygen input has strong impacts on fine ‑ scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands". This study investigated how plant-mediated oxygen input affects subsurface biogeochemical reactions of organic carbon degradation and the resulting methane emissions of coastal wetlands by model simulation. We used the subsurface geochemical simulator PFLOTRAN for the modeling, which produced the simulated changes in porewater chemical substances and methane emissions over 10 days under different scenarios of plant-mediated oxygen input.Specifically, this dataset contains: 1) the input files for PFLOTRAN of all simulation runs conducted in this study. Those files are with an extension of ".in", containing information of the biogeochemical reaction network (stoichiometry, reaction rate, Monod constants, etc), fluid flow rate and oxygen concentration in the fluid which together simulated the plant-mediated oxygen input, the configuration of artificial reactions that simulated the methane fluxes, etc. The PFLOTRAN input files are text files, which can be opened by NotePad, but running these input files will require proper installation of PFLOTRAN (instruction: https://documentation.pflotran.org/user_guide/how_to/installation/installation.html). 2) the raw and processed model output from PFLOTRAN of all simulation runs, and 3) the python scripts used to process the raw model output, including random allocation of root cells, converting raw data into organized formats, calculating the methane fluxes based on the model output, data visualization, etc. The raw and processed model output from PFLOTRAN are in .spydata format, which can be viewed with Python. and 3) the python scripts for data processing and analysis are programming scripts, which can be opened with Python.This modeling work, in particular the model parameterization of root density and initial conditions of porewater concentrations of biogeochemical substances, was based on field measurements at the salt marsh of the Upper Parker River Estuary, Massachusetts, United States.

54 ENVIRONMENTAL SCIENCES↗