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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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DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Reaction and diffusion at the reservoir/shale interface during CO 2 storage: Impact of geochemical kinetics

Here we use a reactive diffusion model to investigate what happens to CO 2 injected into a subsurface sandstone reservoir capped by a chlorite- and illite-containing shale seal. The calculations simulate reaction and transport of supercritical (SC) CO 2 at 348.15 K and 30 MPa up to 20,000 a. Given the low shale porosity (5%), chemical reactions mostly occurred in the sandstone for the first 2000 a with some precipitation at the ss/sh interface. From 2000 to 4000 a, ankerite, dolomite and illite began replacing Mg–Fe chlorite at the sandstone/shale interface. Transformation of chlorite to ankerite is the dominant reaction occluding the shale porosity in most simulations: from 4000 to 7500 a, this carbonation seals the reservoir and terminates reaction. Overall, the carbonates (calcite, ankerite, dolomite), chlorite and goethite all remain close to local chemical equilibrium with brine. Quartz is almost inert from the point of its dissolution/precipitation. However, the rate of quartz reaction controls the long-term decline in aqueous silica activity and its evolution toward equilibrium. The reactions of feldspars and clays depend strongly on their reaction rate constants (microcline is closer to local equilibrium than albite). The timing of porosity occlusion mostly therefore depends on the kinetic constants of kaolinite and illite. For example, an increase in the kaolinite kinetic constant by 0.25 logarithmic units hastened porosity closure by 4300 a. The earliest simulated closure of porosity occurred at approximately 108 a for simulations designed as sensitivity tests for the rate constants. These simulations also emphasize that the rate of CO 2 immobilization as aqueous bicarbonate (solubility trapping) or as carbonate minerals (mineral trapping) in sandstone reservoirs depends upon reaction kinetics – but the relative fraction of each trapped CO 2 species only depends upon the initial chemical composition of the host sandstone. For example, at the point of porosity occlusion the fraction of bicarbonate remaining in solution depends upon the initial Na and K content in the host rock but the fraction of carbonate mineralization depends only on the Ca, Mg, Fe content. Since ankerite is the dominant mineral that occludes porosity, the dissolved concentration of ferrous iron is also an important parameter. Finally, future efforts should focus on cross-comparisons and ground-truthing of simulations made for standard case studies as well as laboratory measurements of the reactivities of clay minerals.

58 GEOSCIENCES↗
DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids

With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.

digital real-time simulation↗
DOE OSTI2018

A Fast Scalable Quasi-Static Time Series Analysis Method for PV Impact Studies Using Linear Sensitivity Model

Understanding the impact of distributed photovoltaic (PV) resources on various elements of the distribution feeder is imperative for their cost effective integration. A year-long quasi-static time series (QSTS) simulation at 1-second granularity is often necessary to fully study these impacts. However, the significant computational burden associated with running QSTS simulations is a major challenge to their adoption. In this paper, we propose a fast scalable QSTS simulation algorithm that is based on a linear sensitivity model for estimating voltage-related PV impact metrics of a three-phase unbalanced, nonradial distribution system with various discrete step control elements including tap changing transformers and capacitor banks. Here, the algorithm relies on computing voltage sensitivities while taking into account all the effects of discrete controllable elements in the circuit. Consequently, the proposed sensitivity model can accurately estimate the state of controllers at each time step and the number of control actions throughout the year. For the test case of a real distribution feeder with 2969 buses (5469 nodes), 6 load/PV time series power profiles, and 9 voltage regulating elements including controller delays, the proposed algorithm demonstrates a dramatic time reduction, more than 180 times faster than traditional QSTS techniques.

14 SOLAR ENERGY↗
DOE OSTI2021

Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results

Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm, which is a controller designed for dampening stop-and-go traffic waves. With more than 1100 miles of driving data collected by our physical platform, we validate our analysis results by comparing it to human driving behaviors. The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration. To expand upon previous analysis, reachability analysis is used to investigate the safety at the speeds it was originally tested and also at higher speeds. Two formulations of safety analysis with different criteria are shown: distance-based and time headway-based. The FollowerStopper is considered safe with distance-based criterion. However, simulation results demonstrate that the FollowerStopper is not representative of human drivers - it follows too closely behind vehicles, specifically at a distance human would deem as unsafe. On the other hand, under the time headway-based safety analysis, the FollowerStopper is not considered safe anymore. A modified FollowerStopper is proposed to satisfy time-based safety criterion. Simulation results of the proposed FollowerStopper shows that its response represents human driver behavior better.

Chou, Fang-Chieh↗
DOE OSTI2024

Results of an In-Field Validation Exercise in Support of Wide-Area Environmental Sampling

The National Nuclear Security Administration’s (NNSA) Office of Nonproliferation and Arms Control (NA-24) is evaluating Wide-Area Environmental Sampling (WAES) as an additional safeguards verification tool for the International Atomic Energy Agency to detect undeclared nuclear activities. The NNSA is evaluating strategies for conducting a generic WAES campaign, the cost of a WAES campaign, and the effect of technological advancements that have occurred since the last major WAES review in 1999. Until now, the NNSA effort has focused on tabletop exercises (TTXs) in which high-performance computing allows for advanced modeling and simulation efforts to be applied to the WAES question. Although the modeling and simulations used in the TTXs are extremely valuable, field campaigns are still needed to validate the assumptions that underpin the models and the modeling process itself. During a 7 week period beginning in May 2023 and ending in June 2023, which included 4 weeks of active field collections, a multilaboratory team conducted its first in-field validation exercise. Prior to the in-field exercise, abbreviated TTXs were conducted to estimate the performance of all collection systems to be used during the field test. These TTXs guided the selection of materials to be released and the placement of the collection system. Based on these determinations, materials were procured to use in the field test, and an injection/release system was designed, built, and installed at the test facility. Background samples were collected during weeks one and four, and environmental collections against active releases were conducted during weeks two and three. The goals of this validation exercise included a demonstration of (1) the ability to provide controlled releases of particulates of surrogate materials, (2) the fielding and operation of collection systems (including deposition and active air collectors), and (3) the flexibility to revise equipment and campaign plans in the field. This paper presents the results and preliminary conclusions for this initial validation test. Based on these results, subsequent field campaigns are anticipated and will include the addition of other released materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Optimized Gen-II FeCrAl cladding production in large quantity for campaign testing

There are two major objectives in this report; (1) to optimize microstructure control of ATF FeCrAl alloys during tube drawing processes, and (2) to provide an update on the progress of ATF FeCrAl tube production via commercial manufacturers. Experimental efforts have been made to optimize the process parameters balancing the tube fabricability, especially for tube drawing processes, and microstructure control of the final tube products. Lab-scale sheet materials of Gen II FeCrAl alloys (Mo-containing and Nb-containing FeCrAl alloys) were used in the study, combined with a stepwise warm-rolling process and intermediate annealing, aiming to simulate the tube drawing process in a commercial tube manufacturer. The intermediate annealing at 650ºC for 1h was suggested for the tube-drawing process of Mo-containing FeCrAl alloys because it successfully softened the material by recovering the work hardening introduced through the rolling step, without inducing grain coarsening due to recrystallization. The final tube product is expected to have stabilized deformed microstructure providing the improved tensile properties with sufficient ductility. Optimization efforts on Nb-containing FeCrAl alloys focused on the effect of alloying additions and annealing conditions on the stability of deformed microstructure. Relationships between the second-phase precipitates (Fe 2 Nb-Laves phase) and microstructure stability are discussed. FeCrAl tube production through commercial tube manufacturers is currently in progress. Three different manufacturers, Century Tubes, Inc. (CTI), Rhenium Alloys, Inc. (RAI), and Superior Tube Company, Inc. (STC), are providing capabilities for cold-drawing, warm-drawing, and HPTR cold-pilgering, respectively. The first two companies are currently working on large quantity tube production (expected 250 ft length) of Gen I model FeCrAl alloy (B136Y3, at CTI) and Gen II (C35M4, at RAI), with the process parameters obtained from the experimental efforts. The expected delivery dates are at the end of July, 2016, and the middle of June, 2016, respectively. Tube production at STC would be the first attempt to apply cold-pilgering to the FeCrAl alloys. Communication has been initiated, and the materials have been machined for the cold-pilgering process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Framework Composition and NH 3 on the Diffusion of Cu + in Cu-CHA Catalysts Predicted by Machine-Learning Accelerated Molecular Dynamics

Cu-exchanged zeolites rely on mobile solvated Cu + cations for their catalytic activity, but the role of the framework composition in transport is not fully understood. Ab initio molecular dynamics simulations can provide quantitative atomistic insight but are too computationally expensive to explore large length and time scales or diverse compositions. We report a machine-learning interatomic potential that accurately reproduces ab initio results and effectively generalizes to allow multinanosecond simulations of large supercells and diverse chemical compositions. Biased and unbiased simulations of [Cu(NH 3 ) 2 ] + mobility show that aluminum pairing in eight-membered rings accelerates local hopping and demonstrate that increased NH 3 concentration enhances long-range diffusion. The probability of finding two [Cu(NH 3 ) 2 ] + complexes in the same cage, which is key for SCR-NOx reaction, increases with Cu content and Al content but does not correlate with the long-range mobility of Cu + . Supporting experimental evidence was obtained from reactivity tests of Cu-CHA catalysts with a controlled chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A labeled dataset for building HVAC systems operating in faulted and fault-free states

Abstract Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Biomimetic composite scaffold from an in situ hydroxyapatite coating on cellulose nanocrystals

A novel nanocomposite scaffold was developed by homogeneous deposition of hydroxyapatite (HAP) on a cellulose nanocrystals (CNCs) matrix suspended in a simulated body fluid (SBF). By adjusting the pH of the SBF, the HAP content in the nanocomposite could be controlled between 15 wt% and 47 wt%. Physical and chemical characteristics of the nanocomposites were analyzed by SEM, FTIR, XRD, SAED, and TEM, which confirmed the successful incorporation of HAP onto the CNCs. The nanocomposites were then freeze-casted into porous scaffolds by different solidification technologies ( i.e. , directional freezing (DF), plunging in liquid N 2 (PL) or in a -20 °C freezer (FZ)) followed by lyophilization. Compression testing of the HAP/CNCs foams indicated that DF caused significant improvement in mechanical properties due to the specific orientation and anisotropic porous structure compared to conventional freezing methods such as PL and FZ. Moreover, the scaffold with high HAP content exhibited improved mechanical and thermal properties, which holds potential for application in bone tissue engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A general framework for quantitatively assessing ecological stochasticity

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio ( NST ), was developed with 50% as the boundary point between more deterministic (<50%) and more stochastic (>50%) assembly. NST was tested with simulated communities by considering abiotic filtering, competition, environmental noise, and spatial scales. All tested approaches showed limited performance at large spatial scales or under very high environmental noise. However, in all of the other simulated scenarios, NST showed high accuracy (0.90 to 1.00) and precision (0.91 to 0.99), with averages of 0.37 higher accuracy (0.1 to 0.7) and 0.33 higher precision (0.0 to 1.8) than previous approaches. NST was also applied to estimate stochasticity in the succession of a groundwater microbial community in response to organic carbon (vegetable oil) injection. Our results showed that community assembly was shifted from more deterministic ( NST = 21%) to more stochastic ( NST = 70%) right after organic carbon input. As the vegetable oil was consumed, the community gradually returned to be more deterministic ( NST = 27%). In addition, our results demonstrated that null model algorithms and community similarity metrics had strong effects on quantifying ecological stochasticity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Distributed Automatic Generation Control Considering DPV Using T&D Dynamic Co-Simulation

The increasing adoption of distributed energy resources (DERs) over the last decade warrants a reconsideration of control of generation resources. This paper proposes a distributed Automatic Generation Control (AGC) using transmission-and-distribution (T&D) dynamic co-simulation framework for the efficient DPV frequency regulation services. The co-simulation framework allows AGC units to exchange the information for distributed AGC, based on their adopted communication network topology. As a result, a cost-effective automatic generation control is achieved with DPV and conventional generators. The proposed distributed AGC is based on the gossip algorithm in which the neighboring AGC units share the relevant local information with each other and updates their share of AGC regulation signal. Distributed photovoltaics (DPV) unit contribute to AGC response based on their headroom capacity via DER aggregators. The algorithm is tested on IEEE-14 bus transmission system under conditions of generation failure and random load variation to observe effective frequency regulations service offered by DPVs and other AGC units. The study shows that DPV can effectively participate in AGC with the proposed distributed control framework.

automatic generation control↗
DOE OSTI2024

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗
DOE OSTI2015

Poole-Frenkel-effect as dominating current mechanism in thin oxide films—An illusion?!

In many of the publications, over 50 per year for the last five years, the Poole-Frenkel-effect (PFE) is identified or suggested as dominating current mechanism to explain measured current–electric field dependencies in metal-insulator-metal (MIM) thin film stacks. Very often, the insulating thin film is a metal oxide as this class of materials has many important applications, especially in information technology. In the overwhelming majority of the papers, the identification of the PFE as dominating current mechanism is made by the slope of the current–electric field curve in the so-called Poole-Frenkel plot, i.e., logarithm of current density, j, divided by the applied electric field, F, versus the square root of that field. This plot is suggested by the simplest current equation for the PFE, which comprises this proportionality (ln(j/F) vs. F{sup 1/2}) leading to a straight line in this plot. Only one other parameter (except natural constants) may influence this slope: the optical dielectric constant of the insulating film. In order to identify the importance of the PFE simulation studies of the current through MIM stacks with thin insulating films were performed and the current–electric field curves without and with implementation of the PFE were compared. For the simulation, an advanced current model has been used combining electronic carrier injection/ejection currents at the interfaces, described by thermionic emission, with the carrier transport in the dielectric, described by drift and diffusion of electrons and holes in a wide band gap semiconductor. Besides the applied electric field (or voltage), many other important parameters have been varied: the density of the traps (with donor- and acceptor-like behavior); the zero-field energy level of the traps within the energy gap, this energy level is changed by the PFE (also called internal Schottky effect); the thickness of the dielectric film; the permittivity of the dielectric film simulating different oxide materials; the barriers for electrons and holes at the interfaces simulating different electrode materials; the temperature. The main results and conclusions are: (1) For a single type of trap present only (donor-like or acceptor-like), none of the simulated current density curves shows the expected behavior of the PFE and in most cases within the tested parameter field the effect of PFE is negligibly small. (2) For both types of traps present (compensation) only in the case of exact compensation, the expected slope in the PF-plot was nearly found for a wider range of the applied electric field, but for a very small range of the tested parameter field because of the very restricting additional conditions: first, the quasi-fermi level of the current controlling particle (electrons or holes) has to be 0.1 to 0.5 eV closer to the respective band limit than the zero-field energy level of the respective traps and, second, the compensating trap energy level has to be shallow. The conclusion from all these results is: the observation of the PFE as dominating current mechanism in MIM stacks with thin dielectric (oxide) films (typically 30 nm) is rather improbable!.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Stochastic correlation analysis to rank the impact of intermittent wind generation on unreliability margins of power systems

Power systems are vulnerable to extreme contingencies (like an outage of a major generating substation or transmission line) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Power systems operators take time-ahead actions (real time to day ahead) actions based on forecasted data as well as telemetry. However, there is a probability of extreme swings in wind generation that can push the power system that is already close to system boundaries into unreliable states. Increasing penetration on wind generation and uncertainties in short term forecast can move the system into operational states that can violate N-1 reliability criteria. While the power system planning accounts for worst case analyses to mitigate such emergencies, it is necessary to understand the spatial and temporal correlation of load buses with intermittent wind generation. The ranking of wind generators based on stochastic correlation to unreliability margins of load buses provides an insight of system vulnerabilities that can be corrected by appropriate emergency controls. A Monte-Carlo simulation of wind uncertainty forecast is performed to identify the probability distributions of unreliability margins. Ranking of wind generators is performed based on stochastic correlation analysis of the wind power generated and the load losses at the buses. This helps in not only identifying weak buses in the power system but also in identifying the vulnerable wind locations to plan for system reinforcements. Power system modeling and hybrid simulation to calculate unreliability margins are performed using DCAT and demonstrated on the 32-bus Nordic test system.

generators, wind forecasting, wind power generatio↗
DOE OSTI2015

Development of realistic physical breast phantoms matched to virtual breast phantoms based on human subject data

Purpose: Physical phantoms are essential for the development, optimization, and evaluation of x-ray breast imaging systems. Recognizing the major effect of anatomy on image quality and clinical performance, such phantoms should ideally reflect the three-dimensional structure of the human breast. Currently, there is no commercially available three-dimensional physical breast phantom that is anthropomorphic. The authors present the development of a new suite of physical breast phantoms based on human data. Methods: The phantoms were designed to match the extended cardiac-torso virtual breast phantoms that were based on dedicated breast computed tomography images of human subjects. The phantoms were fabricated by high-resolution multimaterial additive manufacturing (3D printing) technology. The glandular equivalency of the photopolymer materials was measured relative to breast tissue-equivalent plastic materials. Based on the current state-of-the-art in the technology and available materials, two variations were fabricated. The first was a dual-material phantom, the Doublet. Fibroglandular tissue and skin were represented by the most radiographically dense material available; adipose tissue was represented by the least radiographically dense material. The second variation, the Singlet, was fabricated with a single material to represent fibroglandular tissue and skin. It was subsequently filled with adipose-equivalent materials including oil, beeswax, and permanent urethane-based polymer. Simulated microcalcification clusters were further included in the phantoms via crushed eggshells. The phantoms were imaged and characterized visually and quantitatively. Results: The mammographic projections and tomosynthesis reconstructed images of the fabricated phantoms yielded realistic breast background. The mammograms of the phantoms demonstrated close correlation with simulated mammographic projection images of the corresponding virtual phantoms. Furthermore, power-law descriptions of the phantom images were in general agreement with real human images. The Singlet approach offered more realistic contrast as compared to the Doublet approach, but at the expense of air bubbles and air pockets that formed during the filling process. Conclusions: The presented physical breast phantoms and their matching virtual breast phantoms offer realistic breast anatomy, patient variability, and ease of use, making them a potential candidate for performing both system quality control testing and virtual clinical trials.

60 APPLIED LIFE SCIENCES↗