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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion applications. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery, and the acid dew point is a key parameter for this optimization. Commercially available acid dew point meters use electric conductivity sensors. These sensors are known to greatly underestimate the dew point due to their low sensitivity. In addition, no validation testing has been reported for these units and they are often expensive. In this work, we analyze the theory of the sulfuric acid condensation and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface as the surface temperature of the window is slowly decreased. In this way, an accurate measurement of the dew point is obtained under a wide range of concentrations. The basis of the instrument is that a collimated beam from a diode laser will generate forward scattered light when the beam encounters surface condensate, and a sophisticated array detector is used to sensitively monitor the onset of light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, to calibrate the dew point meter we developed a calibration system based on a liquid bubbler that can generate a stable gas flow with a known sulfuric acid dew point. Test results show that the dew point meter can accurately measure acid dew point over a wide range. For H2SO4 vapor concentrations as low as 6 ppm the acid dew point is measured with an error of only ~1°C. To demonstrate the versatility of this instrument, the dew point meter was adapted for use with a high-pressure flow cell to allow for measurements of the dew point of flue gas from pressurized oxy-fuel combustion in a 100 kWth pressurized reactor.

Cheng, Mao↗
DOE OSTI2024

Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method

Abstract An interface-modified reproducing kernel particle method (IM-RKPM) is introduced in this work to allow for a direct model construction from image pixels of heterogeneous polycrystalline Li-ion battery microstructures. The interface-modified reproducing kernel (IM-RK) approximation is constructed through scaling of a kernel function by a regularized distance function in conjunction with strategic placement of interface node locations. This leads to RK shape functions with either weak or strong discontinuities across material interfaces, suitable for modeling various interface mechanics. With the placement of a triple junction node and distance-based scaling of kernel functions, the resulting IM-RK shape function also possesses proper discontinuities at the triple junctions. This IM-RK approximation effectively remedies the well-known Gibb’s oscillation in the smooth approximation of discontinuities. Different from the conventional meshfree approaches for interface discontinuities, this IM-RK approach is done without additional degrees of freedom associated with the enrichment functions, and it is formulated with the standard procedures in the RK shape function construction. This work focuses on identifying the accuracy and convergence properties of IM-RKPM for modeling the coupled electro-chemo-mechanical system. A linear patch test is formulated and numerically tested for the electro-chemo-mechanical coupled problem with a Butler–Volmer boundary condition representing the physical conditions in Li-ion battery microstructures. This is followed by verification of the optimal rates of convergence of IM-RKPM for solving the coupled problem with higher order solutions. The image-based modeling of Li-ion battery microstructures in the numerical examples demonstrates the applicability of the proposed method to realistic Li-ion battery materials modeling.

25 ENERGY STORAGE↗
DOE OSTI2023

A Real-Time ANPC Inverter Digital Twin with Integrated Design-For-Trust

The demand for renewable energy has increased over the last few years, and so has the demand for greater expectations within the energy market. This increasing trend has been accompanied by more significant usage of internet-connected devices (IoT), leading to critical electrical infrastructure being connected to the internet. Implementing internet connectivity with such devices and systems provides benefits such as improving the system's performance, facilitating irregularity and anomaly mitigation, and providing additional situational awareness for enhanced decision-making. However, enhancing the connected system with IoT introduces a drawback – a greater vulnerability to cyber-attacks. Cyber-attacks targeting critical infrastructure in the electrical sector have occurred in the United States and Ukraine. These cyber-attacks highlight and expose vulnerabilities that a system inherits when connecting to the internet. These attacks left thousands of customers without electricity for hours until operators could regain control of the electric utility grid. Therefore, to address the vulnerabilities of an internet-connected power electronic device, this work focused on the hardware layer of the system. Implementing a cyber-control system inside the hardware layer can significantly reduce the possibility of an attacker patching malicious controller firmware into a photovoltaic grid-connected inverter, thus mitigating the likelihood that the inverter becomes inactive a cyber-attack scenario. With this mitigation technique, if a cyberattack is successful and an attacker gains control of the network, a cyber-defense technique is in place to mitigate the impact of the cyber-attack. This additional protection layer was developed based on an innovative concept known as Digital Twin (DT). A DT, in this case, replicates an Active-Neutral Point Clamped (ANPC) inverter and was designed using a hardware language known as VHDL (Very High-Speed Integrated Circuit Hardware Description Language) and applied to Field-Programmable-GateArray (FPGA). The DT is embedded within the FPGA and contained in a controller board, the UCB (Unified Controller Board), developed by the University of Arkansas electrical engineering team. This UCB also contains two Digital Signal Processors (DSPs) responsible for generating associated signals to control an authentic physical inverter. These DSP signals are received and processed by the FPGA that implements the DT of an ANPC; in other words, it simulates in realtime the expected output of an actual ANPC inverter using the signals from the DSP. When a new firmware is ready to be patched, the DT provides output signals simulating behavior that a real ANPC inverter would generate with the new firmware. The new firmware is tested to check if it meets all the operational requirements established using a Design-For-Trust technique (DFTr). If the new firmware fails in at least one of the DFT tests, it is considered malicious and must be rejected. This work is divided into sections, such as Background, which explains the pieces that were used and the strategy behind this work; Process and Procedure, which explains the methodology that was adopted to prove the reliability and effectiveness of this work; Results and Discussion, where the simulations and results are described and explained; followed by Conclusion and Future work section, which concludes this work and adds possible future projects to continue this work further.

do Amaral Custodio, Paulo Vitor↗
DOE OSTI2025

FY25 status report on the addition of candidate materials in Class B Code Case

This report provides the time-dependent allowable stress calculation strategy leveraging the limited creep rupture tests data generated to support the allowable stress for 100,000 hours in American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section II, Part D. A variable confidence index procedure to extrapolate material properties to support 500,000 hours design life is discussed. Time-dependent allowable stresses for Class B component design and analysis are presented for Grade 1 and Grade 2 of Alloy 625. The presented data extrapolation and allowable stress calculation method will support new material addition using limited creep rupture data in the new ASME Boiler and BPVC, Section III, Division 5, Class B rules.

Part D↗
DOE OSTI2023

On Distribution Grid Optimal Power Flow Development and Integration

Due to changes in electric distribution grid operation, new operation regimes have been recommended. Distribution grid optimal power flow (DOPF) has received tremendous attention in the research community, yet it has not been fully adopted across the utility industry. Our paper recognizes this problem and suggests a development and integration procedure for DOPF. We propose development of DOPF as a three step procedure of 1) processing the grid, 2) obtaining a tractable solution, and 3) implementing multiple solution algorithms and benchmarking them to improve application reliability. For the integration of DOPF, we demonstrate how a DOPF federate may be developed that can be integrated in a co-simulation environment to mimic the real-world conditions and hence improve its practicality to be deployed in the field. To demonstrate the efficacy of the proposed methods, tests on IEEE 123 bus system are performed where the usage of tractable formulation in DOPF algorithm development and its comparison to the benchmark solution are demonstrated.

Hanif, Sarmad↗
DOE OSTI2020

Fast and Accurate Core Analysis by the Full-Immersion Pressure-Pulse Decay: Part 1—Theory

Summary Core-scale measurements are considered the ground truth that oil and gas or electric utility companies use to predict the migration of fluids such as oil, natural gas, carbon dioxide, or brine deep underground during their extraction or injection operations. To provide a greater understanding of petrophysical properties of low-permeability geologic formations such as shales and tight gas sandstones, this study introduces a novel core-analysis procedure. The technique follows conventional pressure-pulse-decay permeametry, where the pressure in an inlet chamber adjacent to a cylindrical core plug undergoes a rapid pressurization, the system is shut in, and the pressure reaches a new equilibrium. However, unlike a standard unidirectional pressure-pulse decay, the full-immersion pressure-pulse decay (Hannon 2019) applies a pressure disturbance to the entire outer surface area of the sample. This article covers the numerical simulator designed to model flow through an anisotropic porous sample in this scenario. The model assumes distinct but uniform permeabilities along the radial and axial directions of the cylindrical plug sample. When extracting a plug vertically (or perpendicular to bedding), the permeability along the radial direction associates with the horizontal permeability (i.e., parallel to bedding), whereas in the axial direction, flow occurs perpendicular to bedding (a vertical permeability). Investigations of these model outputs demonstrate an approximately 20-fold decrease in time to complete a full-immersion experiment compared with conventional pressure-pulse decay. Furthermore, the pressure-decay curves resulting from the full-immersion method have slightly different shapes than those resulting from other unidimensional transient methods. These differences begin to demonstrate that, under achievable experimental conditions, the analysis of pressure data from one full-immersion test could enable the simultaneous estimation of the apparent permeabilities parallel and perpendicular to bedding of a cylindrical sample in addition to its porosity. A follow-up article finalizes the proof of this capability with a parameter-estimation procedure and presents experimental verification through a proof-of-concept study. Described in greater detail in that article, the parameter estimator requires multiple forward simulations to analyze the data, which behooves minimizing the compute time for each simulation. By using an alternating direction implicit time-marching scheme and a structured but variably spaced grid, the numerical simulator built for this purpose provides a forward model output with suitable accuracy in approximately 0.5 seconds.

Energy & Fuels↗
DOE OSTI2021

Analysis of the MST-16 crimp process on cold 304L stainless steel

The purpose of this report is to assess the quality of the MST-16 crimp process through a series of cold experiments and metallographic analyses. Common practice in MST-16 uses a mechanical crimp on 304L stainless steel tubes to prevent radioactive contamination from escaping the tube interior for a variety of experiments. The crimped tubes must pass a leak check to demonstrate their radiological safety. Cold (i.e. non-radioactive samples) 304L tube samples were tested using two different approved crimping devices to assess the quality of the crimps. Each crimp was leak checked, followed by destructive metallographic analysis to determine the quality of both the crimp equipment and procedures used by MST-16 personnel.

42 ENGINEERING↗
DOE OSTI2022

Radiological Considerations Supporting the American Medical Isotope Producer Niowave

This report provides a summary of work performed by Savannah River National Laboratory (SRNL) during FY22 in support of Niowave, an American Medical Isotope Production (AMIP) facility. SRNL served in a technical support role, funded by NA-231, supporting Niowave in the beginning of non radiological functional testing of their airport facility in FY22. Through this agreement, SRNL provides Niowave access to subject matter experts (SMEs) for questions that may arise during the drafting of engineering plans, facility policies, and/or response procedures. This report summarizes discussions between SRNL and Niowave about guidance concerning issues with the floor of the hot cells, dispersible removable contamination (beta emitting fission product), hot cell operation specifically utilization of cameras or mirrors, and the process for removing contaminated waste from the hot cell. Lessons learned and other various resources provided to Niowave by SRNL during FY22 are referenced in this report. This work was funded through NNSA’s Office of Material Management and Minimization, Conversion Office (NA-231).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Recovery and Enhanced Upgrading of Rare Earth Elements from Coal-Based Resources: Bioleaching and Precipitation

Rare earth elements (REEs) are of great importance to modern society and their reliable supply is a major concern of many industries that utilize them in metal alloys, semiconductors, electrical equipment, and defense equipment. REEs in the coal waste have been revealed to be an alternative resource for REEs production. In this study, the extraction, recovery, and upgrading of the REEs from coal waste has been realized with the bioleaching and precipitation processes. Reliable and sustainable acid and oxidant production from the oxidation of the pyrite with Acidithiobacillus ferrooxidans to generate acid for leaching were realized in this research. The acidified bioleaching solution was used to extract REEs from coal waste, with 13–14% yields for most REE elements (~72 h of leaching). However, recovery for longer duration tests was significant higher (varies from 40–60% for individual REEs). After extraction, precipitation and separation processes were designed with the aid of Visual Minteq calculations and modeling to concentrate the REEs. With the procedures designed in this research, a final REEs precipitate product containing 36.7% REEs was produced.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

SULI Internship Deliverables (Flow Orifice Design: Measuring Degas Flow of Experiment Loops at the Advanced Test Reactor)

These deliverables present a design for a new orifice flow meter to be installed in three experiment loops at the Advanced Test Reactor. The current configuration of the experiment loop system has an orifice that is not properly sized to the low flow rates of the degas line of the pressurizer system, causing inaccurate flow measurements. Under consideration of flow conditions and system constraints, an iterative procedure was utilized to determine the optimal sizing for a new orifice. This orifice is designed to accurately and precisely measure the flow rate of the degas line, which will consequently improve control of the pressure and chemistry of the loop pressurizer system. The scope of this project includes recommendations for orifice sizing, material, flange type, face type, and installation location on the loop piping spools. The design is suitable for experiment loops 1D-N, 2B-SE, and 2D-SW and meets all necessary standards.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2024

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗
DOE OSTI2025

Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples

We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter f NL loc via the large-scale scale-dependent bias in the power spectrum using 1,631,716 LRGs (0.6 < z < 1.1) and 1,189,129 QSOs (0.8 < z < 3.1). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative technique allowing the correction through the window matrix convolution. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure f NL loc = -3.6 -9.1 +9.0 at 68% confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to f NL loc = 3.5 -7.4 +10.7 at 68% confidence. Due to restricted selection in the LRG sample, the inclusion of the LRGs allows for 10% improvement. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of 2.3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta $p$ T > $500$ GeV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Storage Field Development Plan: One Earth Energy

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, and operational plans, and costs associated with the proposed One Earth Sequestration Carbon Capture and Storage (OES-CCS) site in McLean County, Illinois, near Gibson City. The proposed storage complex, known as the Mt. Simon Storage Complex, comprises the Cambrian Mt. Simon Sandstone reservoir and the primary seal, the Cambrian Eau Claire Formation. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Ordovician St. Peter Sandstone. Geologic characterization of the Mt. Simon Storage Complex at the OES-CCS site was performed by the Illinois Storage Corridor CarbonSAFE Phase III project, which also prepared and submitted three UIC Class VI applications to construct three injection wells; the permit applications were submitted and are in the federal EPA review process. A characterization well, OEE #1, was drilled to collect site-specific data. These data were analyzed and used to develop the UIC Class VI applications. The OEE #1 well will be converted to an in-zone monitoring (IZM) well for the injection phase. The proposed buildout for the OES-CCS site includes (1) three injection wells (OES #1, OES #2, and OES #3), (2) two IZM wells, (3) two above confining zone (ACZ) monitoring wells, one of which will be used to monitor the lowermost USDW, (4) capture and compression facilities, and (5) transportation facilities, i.e., pipelines. A pre-operational testing program was proposed in the Class VI permit application and will be employed at the site pending approval. Additional pre-injection (baseline), syn-injection, and post-injection monitoring and site care procedures will be followed by OES to ensure that injection activities are protective of human health and the environment. Injection is scheduled to begin in 2025, distributed across the three injection wells in accordance with the permit operating conditions. One Earth Sequestration intends to inject up to 90 million tonnes of CO 2 over a period of approximately 20 years. Injection will begin at approximately 0.5 million tonnes of CO 2 annually and ramp up to a maximum of 4.5 million tonnes annually. Daily injection rates are expected to range from 1,400 to 1,500 tonnes per day initially and reach a maximum of approximately 4,225 tonnes per day, depending on site geology and injectivity at each injection well location, and CO 2 availability. The costs associated with the OES-CCS project include pre-operational costs (e. g. additional seismic data acquisition and well drilling), capture and transportation facility and equipment costs, predicted field operating expenditures (OpEx), and decommissioning and post-injection site care (PISC) costs. The risks associated with project activities, such as site construction, injection operations, and verification of secure storage were evaluated, and mitigation strategies proposed to alleviate those risks.

09 BIOMASS FUELS↗
DOE OSTI2026

A 3D-Printed Millimeter-Wave Inline Waveguide-to-Coplanar-Waveguide Transition to Enable Dense Spectrometer Arrays for Intensity Mapping Surveys

We present a 3D-printed millimeter-wave, octave-bandwidth, in-line waveguide-to-coplanar-waveguide transition designed to enable focal planes with dense arrays of on-chip spectrometers. These arrays will enable compelling surveys of the large-scale structure of the universe through millimeter-wave intensity mapping. The transition consists of a four-step ridge-waveguide transformer that couples light from a rectangular waveguide onto a coplanar waveguide via an electrical connection made with indium bump bonds. We develop a tolerance-aware optimization approach to identify high-performance transition geometries that are robust to manufacturing variations; the same formulation can be applied to other tolerance-sensitive design problems. We also describe the implementation of a custom apparatus and procedure for bump-bonding a silicon chip to a metallized 3D-printed component. We detail the fabrication of the coplanar waveguide chip and three-dimensional waveguide structure, simulations and metrology of a test device, and room temperature reflectance measurements of this device. The room temperature metrology and reflection measurements are consistent with a model that predicts a coupling efficiency of $\mathord{\sim} 95\%$ at cryogenic temperatures in the 85-170 GHz frequency range.

Stover, Austin [Chicago U.; Chicago U., KICP] (ORC↗
DOE OSTI2021

Recycled polyethylene and crumb rubber composites modified asphalt with improved aging resistance and thermal stability

Crumb rubbers (CR) and recycled Polyethylene (PE) are commonly used as modifiers to improve the asphalt properties. However, the addition of these modifiers individually may result in phase separation of PE and inadequate degradation of CR, which may not simultaneously satisfy the rheological and aging resistance of the binder blends. In this study, a type of CR/PE composites manufactured through melt extrusion procedures was adopted for the improvement of the modified binder blends. The modified binder blends after short-term (RTFO) and long-term (PAV) aging were collected for dynamic shear rheometer and bending beam rheometer tests. FTIR tests were also used to quantify the aging resistance, while differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were applied to evaluate the thermal behaviors of the binder blends. Optical microscopy tests were used to explore the modification mechanism and visualize the microstructures of original and PAV aged binder blends. Test results showed that CR/PE composites could significantly improve the aging resistance of the binder blends. The dispersed PE particles still interacted with each other and meanwhile worked with the diffused rubbery phase, which could form a similar TPEs network. The oxidation and high-temperature aging of such binder blends would strengthen the network that resisted the aging severity of the binder blends. Furthermore, it was also revealed that CR/PE modified asphalt could sustain more heat before a rapid degradation and the well-dispersed PE particles could interact with the diffused CR particles to form a network to resist aging.

02 PETROLEUM↗
DOE OSTI2024

Development of a Distribution Optimal Power Flow Federate for Open-Source OEDI-SI Platform

Increasing numbers of distributed generators in the electric power distribution networks require developing a control strategy to optimize solutions in real time. Linearized optimal distribution flow development has seen growth and acceptance in the distribution systems literature for efficiently modeling the \glspl{opf} for distribution systems. This paper examines the implementation and integration procedure for linearized optimal distribution flow federate to \gls{oedisi} platform. Specifically, we discuss i) the usage of the \gls{oedisi} platform, ii) obtaining a tractable solution using developed \gls{opf} federate, and iii) validation of solutions and bench-marking the \gls{oedisi} platform with developed \gls{opf} federate using OpenDSS. In brief, we demonstrate how a general linearized optimal distribution flow federate can be developed and integrated with a co-simulation environment to mimic real-world examples. The efficacy of the proposed method is demonstrated using the IEEE 123-bus test system under different scenarios to obtain a tractable solution and compare its results.

Sadnan, Rabayet↗