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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Solvation Thermodynamics of Solutes in Water and Ionic Liquids Using the Multiscale Solvation-Layer Interface Condition Continuum Model

We report molecular assembly processes are generally driven by thermodynamic properties in solutions. Atomistic modeling can be very helpful in designing and understanding complex systems, except that bulk solvent is very inefficient to treat explicitly as discrete molecules. The SLIC/CDC multiscale model combines continuum solvent electrostatics based on the solvent layer interface condition (SLIC) with statistical thermodynamic models for hydrogen bonding and nonpolar modes: cavity formation, dispersion interactions, combinatorial mixing (CDC). The SLIC/CDC model predicts Gibbs energies of solvation for a database of 500 solutes in water with average accuracy better than 1 kcal/mol both for experimental measurements and for explicit-solvent molecular dynamics simulations. The separate SLIC/CDC energy mode values agree quantitatively with those computed from explicit-solvent molecular dynamics. The SLIC/SASA multiscale model combines the SLIC continuum electrostatic model with the solvent accessible surface area (SASA) nonpolar energy mode. The SLIC/SASA model predicts Gibbs energies of solvation with better than 1.4 kcal/mol average accuracy in aqueous systems and better than 1.6 kcal/mol average accuracy in ionic liquids. Both models predict solvation entropies, and are the first implicit-solvation models capable of predicting solvation heat capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Enhancement of Extraction of Uranium from Seawater – Final Report

Even at a concentration of 3 μg/L, the world’s oceans contain a thousand times more uranium than currently know terrestrial sources. In order to take advantage of this stockpile, methods and materials must be developed to extract it efficiently, a difficult task considering the very low concentration of the element and the competition for extraction by other atoms in seawater such as sodium, calcium, and vanadium. The majority of current research on methods to extract uranium from seawater are vertical explorations of the grafting of amidoxime ligand, which was originally discovered and promoted by Japanese studies in the late 1980s. Our study expands on this research horizontally by exploring the effectiveness of novel uranium extraction ligands grafted to the surface of polymer substrates using radiation. Through this expansion, a greater understanding of uranium binding chemistry and radiation grafting effects on polymers has been obtained. While amidoxime-functionalized fabrics have been shown to have the greatest extraction efficiency so far, they suffer from an extensive chemical processing step which involves treatment with powerful basic solutions. Not only does this add to the chemical waste produced in the extraction process and add to the method’s complexity, but it also significantly impacts the regenerability of the amidoxime fabric. The approach of this project has been to utilize alternative, commercially available monomers capable of extracting uranium and containing a carbon-carbon double bond to allow it to be grafted using radiation, specifically phosphate, oxalate, and azo monomers. The use of commercially available monomers and radiation grafting with electron beam or gamma irradiation will allow for an easily scalable fabrication process once the technology has been optimized. The need to develop a cheap and reliable method for extracting uranium from seawater is extremely valuable to energy independence, and will extend the quantity of uranium available to the nuclear power industry far into the future. The development of this technology will also promote science in relation to the extraction of other elements from seawater, which could expand the known stockpiles of other highly desirable materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Enhancement of Extraction of Uranium from Seawater

Even at a concentration of 3 μg/L, the world’s oceans contain a thousand times more uranium than currently know terrestrial sources. In order to take advantage of this stockpile, methods and materials must be developed to extract it efficiently, a difficult task considering the very low concentration of the element and the competition for extraction by other atoms in seawater such as sodium, calcium, and vanadium. The majority of current research on methods to extract uranium from seawater are vertical explorations of the grafting of amidoxime ligand, which was originally discovered and promoted by Japanese studies in the late 1980s. Our study expands on this research horizontally by exploring the effectiveness of novel uranium extraction ligands grafted to the surface of polymer substrates using radiation. Through this expansion, a greater understanding of uranium binding chemistry and radiation grafting effects on polymers has been obtained. While amidoxime-functionalized fabrics have been shown to have the greatest extraction efficiency so far, they suffer from an extensive chemical processing step which involves treatment with powerful basic solutions. Not only does this add to the chemical waste produced in the extraction process and add to the method’s complexity, but it also significantly impacts the regenerability of the amidoxime fabric. The approach of this project has been to utilize alternative, commercially available monomers capable of extracting uranium and containing a carbon-carbon double bond to allow it to be grafted using radiation, specifically phosphate, oxalate, and azo monomers. The use of commercially available monomers and radiation grafting with electron beam or gamma irradiation will allow for an easily scalable fabrication process once the technology has been optimized. The need to develop a cheap and reliable method for extracting uranium from seawater is extremely valuable to energy independence and will extend the quantity of uranium available to the nuclear power industry far into the future. The development of this technology will also promote science in relation to the extraction of other elements from seawater which could expand the known stockpiles of other highly desirable materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

ZAM Modeling Study to Support the Tank Closure Cesium Removal (TCCR) 1A Unit

Currently at the Savannah River Site (SRS), the Tank Closure Cesium Removal (TCCR) is an “at-tank” process designed to remove cesium from aqueous tank waste. Cesium will be removed by ion exchange using the engineered IONSIV® R9120 form of Crystalline Silicotitanate (CST) media. The current TCCR design has two columns online in a lead-lag configuration to optimize media usage and achieve the target decontamination. Once the lead column is saturated with cesium, it will be removed from service, the lag column will rotate into the lead position, and a new column with fresh ion-exchange media will be placed into the lag position. The TCCR process for cesium removal from Tank 10H is detailed in X-SOW-H- 00002. Demonstration of the system began in early calendar year 2019 with two batches of salt solution generated by dissolving saltcake in Tank 10H, followed by processing of these batches through the TCCR system. A third TCCR Tank 10H dissolved saltcake batch is scheduled for processing soon. Upon completion of the demonstration with Tank 10H dissolved saltcake, Tank 9H salt solution will be transferred to Tank 10H and subsequently processed through the TCCR unit with new CST media (referred to as R9120-B 30x60) added to new IX columns. The TCCR processing campaign of Tank 9H salt solution is referred to as TCCR-1A .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Coupled Hydrothermal Extraction and Ligand-Associated Swellable Glass Media Recovery of Rare Earth Elements from Coal Fly Ash (Final Report)

Wayne State University (WSU) researchers, in collaboration with the University of California-Los Angeles (UCLA) and Los Alamos National Laboratory (LANL), have successfully developed a new sorbent media used in a process that concentrated the rare earth content in a coal fly ash sample from southeast MI by >350×, resulting in >13 wt% REO powder. The project developed a new DTPA-associated media that was used to concentrate total REEs. This project demonstrated a coupled hydrothermal extraction and solid-liquid recovery process that produced REO powder from raw fly ash while nearly eliminating the use of organic solvents. The project successfully: 1) identified a commercially viable ash supply with >$2.5 M in REO value being deposited monthly, 2) hydrothermally extracted >77% of REEs in coal fly ash (20% more than acid alone), 3) developed a new sorbent media that was used to concentrate REEs, 4) and engineered a process that resulted in a >13 wt% REO powder. The media also demonstrates a selectivity for mid and heavy REEs over Ce and La and the potential for use in separating individual rare earth elements. An invention disclosure for the sorbent media has been filed with WSU and a patent application will be submitted in the near future. The project examined the potential to couple hydrothermal leaching of coal fly ash with the engineering of a custom ligand-associated media to provide an organic solvent-free method of extracting and recovering REEs. Fly ash feedstock was collected from Detroit area coal-fired power plants, characterized for REE content, and subjected to a bench-top batch hydrothermal leaching/dissolution process inside custom-build pressure reactors at Los Alamos National Laboratory (LANL). This process applied a dissolution technique previously developed to process spent nuclear fuel and other nuclear materials. The modified ash was acidified and the resulting leachate was enriched with REEs along with Ca, Al, and Si. Ligands known to be effective in lanthanide/actinide separation were evaluated based on a series of criteria such as selectivity and association to organosilica through hydrophobicity. Batch experiments were conducted to establish the best conditions (e.g., pH, eluent, etc.) and best ligand systems for the effective extraction of REEs from the alkaline feed solution obtained from the hydrothermal leaching process. Once the organosilica-ligand extraction media was developed for REE concentration, an acidic solution was used to back extract and concentrate the REEs into a heavily REE-laden strip solution. The REEs in the strip solution were precipitated with oxalate to produce rare earth oxides.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Anodic processes in the chemical and electrochemical etching of Si crystals in acid-fluoride solutions: Pore formation mechanism

The interaction of heavily doped p- and n-type Si crystals with hydrofluoric acid in the dark with and without contact with metals having greatly differing work functions (Ag and Pd) is studied. The dependences of the dissolution rates of Si crystals in HF solutions that contain oxidizing agents with different redox potentials (FeCl{sub 3}, V{sub 2}O{sub 5} and CrO{sub 3}) on the type and level of silicon doping are determined. Analysis of the experimental data suggests that valence-band holes in silicon are not directly involved in the anodic reactions of silicon oxidation and dissolution and their generation in crystals does not limit the rate of these processes. It is also shown that the character and rate of the chemical process leading to silicon dissolution in HF-containing electrolytes are determined by the interfacial potential attained at the semiconductor–electrolyte interface. The mechanism of electrochemical pore formation in silicon crystals is discussed in terms of selfconsistent cooperative reactions of nucleophilic substitution between chemisorbed fluorine anions and coordination- saturated silicon atoms in the crystal subsurface layer. A specific feature of these reactions for silicon crystals is that vacant nonbonding d{sup 2}sp{sup 3} orbitals of Si atoms, associated with sixfold degenerate states corresponding to the Δ valley of the conduction band, are involved in the formation of intermediate complexes. According to the suggested model, the pore-formation process spontaneously develops in local regions of the interface under the action of the interfacial potential in the adsorption layer and occurs as a result of the detachment of (SiF{sub 2}){sub n} polymer chains from the crystal. Just this process leads to the preferential propagation of pores along the <100> crystallographic directions. The thermodynamic aspects of pore nucleation and the effect of the potential drop across the interface, conduction type, and free-carrier concentration in the crystal on the pore size and structure are discussed. The concepts developed in the study can consistently account for experimental facts characterizing the etching of silicon crystals with various electrical parameters under various conditions providing the anodic polarization of crystals in HF-containing solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Thermal activation mechanisms and Labusch-type strengthening analysis for a family of high-entropy and equiatomic solid-solution alloys

To understand the underlying strengthening mechanisms, thermal activation processes are investigated from stress-strain measurements with varying temperatures and strain rates for a family of equiatomic quinary, quaternary, ternary, and binary, face-center-cubic-structured, single phase solid-solution alloys, which are all subsystems of the FeNiCoCrMn high-entropy alloy. Our analysis suggests that the Labusch-type solution strengthening mechanism, rather than the lattice friction (or lattice resistance), governs the deformation behavior in equiatomic alloys. First, upon excluding the Hall-Petch effects, the activation volumes for these alloys are found to range from 10 to 1000 times the cubic power of Burgers vector, which are much larger than that required for kink pairs (i.e., the thermal activation process for the lattice resistance mechanism in body-center-cubic-structured metals). Second, the Labusch-type analysis for an N-element alloy is conducted by treating M-elements (M < N) as an effective medium and summing the strengthening contributions from the rest of N-M elements as individual solute species. For all equiatomic alloys investigated, a qualitative agreement exists between the measured strengthening effect and the Labusch strengthening factor from arbitrary M to N elements based on the lattice and modulus mismatches. Furthermore, the Labusch strengthening factor provides a practical critique to understand and design such compositionally complex but structurally simple alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Inferring the Dynamics of the State Evolution During Quantum Annealing

To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we propose to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Furthermore, using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called "slicing", we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits.

42 ENGINEERING↗
DOE OSTI2019

A graph theoretic framework for representation, exploration and analysis on computed states of physical systems

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial differential equations, with solutions being obtained by computation. The motivation is to gain insight that may otherwise be difficult to attain because of the high dimensionality of computed solutions. We consider graph theoretic representations that are made possible by low-dimensional states defined on the systems. These states are typically functionals of the high-dimensional solutions, and therefore retain important aspects of the high-fidelity information present in the original, computed solutions. Our method is rooted in regarding each state as a vertex on a graph and identifying edges via processes that are induced either by numerical solution strategies, or by the physics. Correspondences are drawn between the sampling of stationary states, or the time evolution of dynamic phenomena, and the analytic machinery of graph theory. A collection of computations is examined in this framework and new insights to them are presented through analysis of the corresponding graphs.

42 ENGINEERING↗
DOE OSTI2025

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗
DOE OSTI2018

WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes

Computational fluid dynamics (CFD)-based wear predictions are computationally expensive to evaluate, even with a high-performance computing infrastructure. Thus, it is difficult to provide accurate local wear predictions in a timely manner. Data-driven approaches provide a more computationally efficient way to approximate the CFD wear predictions without running the actual CFD wear models. In this paper, a machine learning (ML) approach, termed WearGP, is presented to approximate the 3D local wear predictions, using numerical wear predictions from steady-state CFD simulations as training and testing datasets. The proposed framework is built on Gaussian process (GP) and utilized to predict wear in a much shorter time. The WearGP framework can be segmented into three stages. At the first stage, the training dataset is built by using a number of CFD simulations in the order of O (10 2 ). At the second stage, the data cleansing and data mining process are performed, where the nodal wear solutions are extracted from the solution database to build a training dataset. At the third stage, the wear predictions are made, using trained GP processes. Two CFD case studies including 3D slurry pump impeller and casing are used to demonstrate the WearGP framework, in which 144 training and 40 testing data points are used to train and test the proposed method, respectively. The numerical accuracy, computational effiency and effectiveness between the WearGP framework and CFD wear model for both slurry pump impellers and casings are compared. It is shown that the WearGP framework can achieve highly accurate results that are comparable with the CFD results, with a relatively small size training dataset, with a computational time reduction in an order of 10 5 to 10 6 .

42 ENGINEERING↗
DOE OSTI2025

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Methods and systems for utilizing carbide lime or slag

Provided herein are methods comprising a) treating a slag solid or carbide lime suspension with an ammonium salt in water to produce an aqueous solution comprising calcium salt, ammonium salt, and solids; b) contacting the aqueous solution with carbon dioxide from an industrial process under one or more precipitation conditions to produce a precipitation material comprising calcium carbonate and a supernatant aqueous solution wherein the precipitation material and the supernatant aqueous solution comprise residual ammonium salt; and c) removing and optionally recovering ammonia and/or ammonium salt using one or more steps of (i) recovering a gas exhaust stream comprising ammonia during the treating and/or the contacting step; (ii) recovering the residual ammonium salt from the supernatant aqueous solution; and (iii) removing and optionally recovering the residual ammonium salt from the precipitation material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Study of formation mechanism of incipient melting in thixo-cast Al–Si–Cu–Mg alloys

Mechanical properties of thixo-cast Al–Si–Cu–Mg alloys can be enhanced by T61 heat treatment. Copper and magnesium atoms in aluminum matrix can form homogeneously distributed precipitations after solution and aging treatment which harden the alloys. However, microsegregation of these alloying elements could form numerous tiny multi-compound phases during solidification. These phases could cause incipient melting defects in subsequent heat treatment process and degrade the macro-mechanical properties of productions. This study is to present heterogeneous distribution of Cu, Si, and Mg elements and formation of incipient melting defects (pores). In this study, incipient melting pores that occurred during solution treatment at various temperatures, even lower than common melting points of various intermetallic phases, were identified, in terms of a method of investigating the same surface area in the samples before and after solution treatment in a vacuum environment. The results also show that the incipient melting mostly originates at the clusters with fine intermetallic particles while also some at the edge of block-like Al{sub 2}Cu. The fine particles were determined being Al{sub 2}Cu, Al{sub 5}Cu{sub 2}Mg{sub 8}Si{sub 6} and Al{sub 8}Mg{sub 3}FeSi{sub 2}. Tendency of the incipient melting decreases with decreases of the width of the clusters. The formation mechanism of incipient melting pores in solution treatment process was discussed using both the Fick law and the LSW theory. Finally, a criterion of solution treatment to avoid incipient melting pores for the thixo-cast alloys is proposed. - Highlights: • In-situ comparison technique was used to analysis the change of eutectic phases. • The ralationship between eutectic phase size and incipient melting was studied. • Teat treatment criterion for higher incipient melting resistance was proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Experimental and numerical study of the effects of solution concentration and temperature on concrete under external sulfate attack

The work reports on an experimental programme, conducted to validate comprehensively our previously proposed coupled chemo-transport model for external sulfate attack on concrete. Specifically, the effects of the concentration of sulfate solution and temperature on the distribution of sulfate ions in concrete are experimentally investigated and used to demonstrate the accuracy of the modeling framework. Further, the profile of aluminate depletion and the leaching depth numerically are investigated. For all cases the model predictions are in good agreement with the experimental results, showing increases of the concentration of sulfate ions in concrete with higher concentrations of sulfate solution and higher temperatures. It is concluded that higher sulfate solution concentration and temperature enhance the processes involved in the external sulfate attack on concrete, namely diffusion of sulfate ions and their chemical reactions with concrete. It is found that these parameters affect the external sulfate attack predominantly via the chemical reaction process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward

The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.

Pappas, Iosif↗
DOE OSTI2019

A Hermitian symmetric space Fokas–Lenells equation: Solitons, breathers, rogue waves

Highlights: • We study a Hermitian symmetric space Fokas–Lenells equation. • We obtain multi-soliton, kink–breather and rogue wave solutions for this equation. • We analyse the dynamical behaviour of these exact solutions. - Abstract: Based on the zero-curvature representation, we propose a Hermitian symmetric space Fokas–Lenells equation associated with a 4 × 4 matrix spectral problem. Resorting to the gauge transformation between spectral problems, we find a restrictive condition of the spectral functions that can ensure the symmetry of the new potential matrix, from which n-fold classical Darboux transformations and N-fold generalized Darboux transformations of this equation are constructed with the help of the limit technique and an iterative procedure. Utilizing the Darboux transformations and Mathematica software, we obtain various solutions for the Hermitian symmetric space Fokas–Lenells equation, including the multi-soliton solution, kink–breather solution, eye-shaped rogue wave solution, one-peaky shaped rogue wave solution, and dark two-peaky shaped rogue wave solution. By varying the values of the free parameters, we obtain different types of spatial–temporal distribution structures for the solutions, including the fundamental, line and triangular patterns. Furthermore, the dynamical behaviour of these solutions, including the fusion and fission processes of rogue waves, is analysed in detail.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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↗