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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mineral Recovery Enhanced Desalination (MRED) process: An innovative technology for desalinating hard brackish water

Desalination of water containing high concentrations of calcium, dissolved carbon dioxide, sulfate, silica and other sparingly soluble salts is difficult because of the scaling potential. An innovative pre-treatment scheme was investigated at bench scale that selectively removes these constituents and produces a soft water to enable desalination with high feed water recovery. The process first removes dissolved carbon dioxide by air stripping at low pH. Magnesium is removed by precipitation at high pH. Calcium is removed by ion exchange (IX), and sulfate is removed by nanofiltration (NF). Cation regenerant from IX, containing calcium, and concentrate from NF, containing sulfate, is combined to precipitate gypsum. Concentrate from the desalination process consisting of a concentrated NaCl solution is used to regenerate the IX resins. The selective precipitation, IX, and NF processes were tested in laboratory experiments and produced magnesium hydroxide and gypsum at greater than 90% and 95% purity respectively. A process model was developed to calculate process performance, mass and liquid flow rates. Finally, the MRED process offers the following benefits: 1) greater recovery of brackish feedwater by a desalination process, 2) recovery of marketable commodities and 3) reduction in the volume and mass of waste products from the treatment process.

42 ENGINEERING↗
DOE OSTI2018

Internal influences of hydrolysis conditions on rutile TiO2 pigment production via short sulfate process

Highlights: • A novel short sulfate process was proposed to produce rutile TiO{sub 2} pigment. • Effects and internal influences of hydrolysis conditions were investigated in detail. • Intrinsic relationship between hydrolysis conditions and pigment properties were revealed. - Abstract: Rutile TiO{sub 2} white pigment was prepared via short sulfate process by using the unenriched industrial TiOSO{sub 4} solution as titanium source through authigenic seed hydrolysis process. The effects and internal influences of hydrolysis conditions on the structure, particle size distribution and pigment properties for the as-synthesized samples were investigated, involving the inducing hydrolysis water volume ratio, ripening time and hydrolysis time after the second boiling point. These hydrolysis factors influenced the number and quality of the initial formed hydrolysis nuclei, the crystal growth and the particle aggregation velocity, eventually determined the pigment properties. And the conditions had internal mathematical regression correlation with crystal structure, particle polydispersity index and pigment properties. The optimal inducing hydrolysis water volume ratio is of 0.123, ripening time is of 29.05 min, and hydrolysis time is of 2.6 h.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Exploring the kinetics of actinyl–EDTA reduction by ferrous iron using quantum-mechanical calculations

Here, the reduction of An(VI) (An = U, Np, and Pu) to An(IV) significantly decreases its solubility and mobility. This reaction can be hindered by complexation with inorganic (e.g., carbonate) or organic ligands. Ethylenediaminetetraacetic acid (EDTA) is one such organic ligand that forms stable complexes with actinides. Therefore, it may enhance the mobility of actinides. However, the redox kinetics and mechanisms of actinyl (An(V/VI)O 2 +/2+ )–EDTA are not well characterized yet and are thus studied here using quantum-mechanical calculations. The principle is to approach the actinyl–EDTA and Fe 2+ (reductant) in small incremental steps and calculate the system energy at each distance. The overall reaction is then delineated into sub-processes (encounter frequency in bulk solution, formation of outer-sphere complex, transition from outer- to inner-sphere complex, and electron transfer), and reaction rates are determined for each sub-process. The formation of outer-sphere complexes occurs rapidly in microseconds to seconds over a wide range of actinyl concentrations (pM to μM); in contrast, the transition to the inner-sphere complex is relatively slow (milliseconds to a few seconds). Immediate electron transfer to form the pentavalent actinide is observed along the reaction path for Np(VI) and Pu(VI), but not for U(VI). Surprisingly, in acidic conditions, one of the carboxylic groups gets protonated in EDTA of [UO 2 (edta)] 2- rather than one of the amino groups. This process-based series of calculations can be applied to any redox reaction and allows the prediction of changes to the rate law and rate-limiting step in a more fundamental way for different environments

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

Stabilization of an Unprecedented Hexanuclear Secondary Building Unit in a Thorium-Based Metal–Organic Framework

The crystal structures of thorium clusters are important for understanding the formation and transformation mechanisms of actinide species in solution, which can in turns benefit nuclear waste processing and management. However, stabilizing thorium clusters in aqueous solution is quite challenging because of their fast olation and oxolation reactions. Here, we report a thorium-based meta-organic framework, NU-905, with the formula [Th 6 (μ 3 -O) 2 (HCOO) 4 (H 2 O) 6 ] [TCPP = tetrakis(4-carboxyphenyl)porphyrin], synthesized by a solvothermal reaction in N,N-dimethylformamide and water at 120 °C. NU-905 contains a hexanuclear secondary building unit (SBU), [Th 6 (μ 3 -O) 2 (HCOO) 4 (H 2 O) 6 ], which has never been reported previously. The SBUs are capped and bridged by the tetratopic linker TCPP to form a three-dimensional network with scu topology. The activated NU-905 exhibits permanent porosity and shows high catalytic activity for the selective photooxidation of a mustard gas simulant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Scale Up of Malonic Acid Fermentation Process: Cooperative Research and Development Final Report, CRADA Number CRD-16-612

The goal of this work is to use the large fermentation vessels in the National Renewable Energy Laboratory's (NREL) Integrated Biorefinery Research Facility (IBRF) to scale-up Lygos' biological-based process for producing malonic acid and to generate performance data. Initially, work at the 1 L scale validated successful transfer of Lygos' fermentation protocols to NREL using a glucose substrate. Outside of the scope of the CRADA with NREL, Lygos tested their process on lignocellulosic sugars produced by NREL at Lawrence Berkeley National Laboratory's (LBNL) Advanced Biofuels Process Development Unit (ABPDU). NREL produced these cellulosic sugar solutions from corn stover using a separate cellulose/hemicellulose process configuration. Finally, NREL performed fermentations using glucose in large fermentors (1,500- and 9,000-L vessels) to intermediate product and to demonstrate successful performance of Lygos' technology at larger scales.

09 BIOMASS FUELS↗
DOE OSTI2019

Method to produce water-soluble sugars from biomass using solvents containing lactones

A process to produce an aqueous solution of carbohydrates that contains C6-sugar-containing oligomers, C6 sugar monomers, C5-sugar-containing oligomers, C5 sugar monomers, or any combination thereof is presented. The process includes the steps of reacting biomass or a biomass-derived reactant with a solvent system including a lactone and water, and an acid catalyst. The reaction yields a product mixture containing water-soluble C6-sugar-containing oligomers, C6-sugar monomers, C5-sugar-containing oligomers, C5-sugar monomers, or any combination thereof.

Dumesic, James A.↗
DOE OSTI2018

Preparation and Thermal Expansion of Calcium Iron Zirconium Phosphates with the NaZr{sub 2}(PO{sub 4}){sub 3} Structure

Ca{sub 0.5(1+} {sub x)}Zr{sub 2–x}Fe{sub x}(PO{sub 4}){sub 3} phosphates have been synthesized by a sol–gel process. The individual compounds and solid solutions obtained crystallize in the NaZr{sub 2}(PO{sub 4}){sub 3} structure (trigonal symmetry, sp. gr. R3̄). Using high-temperature X-ray diffraction, we have determined their thermal expansion parameters in the temperature range from 25 to 800°C. With increasing x, the magnitudes of their linear thermal expansion coefficients and thermal expansion anisotropy decrease. Most of the synthesized phosphates can be rated as low-thermal-expansion compounds and can be regarded as materials capable of withstanding thermal “stress.”.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles

Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils’ inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Two Modes of the Self-Similar Evolution of Charged Plasma

Two self-similar modes of evolution of charged particles’ high-current beam are described analytically. The situation being considered falls within the field of nonneutral plasma electrodynamics. The process is considered in terms of the nonlinear 1D evolution of the charge density w(x, t) in the channel of a longdistance transmission line with nonlinearly distributed resistance R, capacitance C, and inductance L: R = R(w), C = C(w), and L = 0. It is shown that initially the front of w(x, t) accelerates and then slows down. The description of the process in the channel is based on the charge conservation law. An idealized “kinematic” approach is used according to which an equation in two unknowns (charge density and current density in the channel) can be reduced to an equation in one unknown w(x, t). A strongly nonlinear wave process is studied. A discontinuous solution w(x, t) is constructed with a zero boundary condition at infinity. Such a model description can apply only for revealing the main qualitative features of a complex process. Analytical expressions for the variation in the evolution of the front velocity and perturbed area length are derived. An interrelation between the nonlinearity parameter of the process and the amount of charge in the interelectrode gap is suggested based on the experimental data for the evolution of streamers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Effect of Adsorbed Carboxylates on the Dissolution of Boehmite Nanoplates in Highly Alkaline Solutions

Understanding the dissolution of boehmite in highly alkaline solutions is important to the processing of the complex nuclear wastes stored at the Hanford (WA) and Savannah River (SC) sites. Here, we report the adsorption of model carboxylate anions on boehmite nanoplates in alkaline solutions and their effects on subsequent boehmite dissolution in 3 M NaOH at 80 °C. Although expectedly lower than at circumneutral pH, adsorption of oxalate at pH 13 at room temperature was significant and remained so through a linear decrease to 3 M NaOH conditions with no evidence for the appearance of new phases. Modeling of the adsorption data and rate were consistent with the formation of outer-sphere surface complexes. By using these conditions to preload the boehmite nanoplates with oxalate, and separately acetate, we measured and compared their dissolution behavior at 80 °C and observed a clear suppression of the dissolution rate for the case of adsorbed oxalate by 23% and for adsorbed acetate by 10% compared to pure solids. Ex situ scanning electron microscopy (SEM) and transmission electron microscopy (TEM) characterization revealed no detectable difference in the morphologic evolution of the dissolving boehmite materials. In conclusion, we nonetheless conclude that pre-adsorbed carboxylate anions, even as nominally weakly bound outer-sphere complexes, can persist on the surface through highly alkaline conditions, decreasing the density of dissolution-active sites and thereby adding an extrinsic control on the dissolution rate.

Adsorption kinetics↗
DOE OSTI2023

Data-Driven Approaches for Bead Geometry Prediction Via Melt Pool Monitoring

In the realm of additive manufacturing, the selection of process parameters to avoid over and under deposition entails a time-consuming and resource-intensive trial-and-error approach. Given the distinct characteristics of each part geometry, there is a pressing need for advancing real-time process monitoring and control to ensure consistent and reliable part dimensional accuracy. Here, this research shows that support vector regression (SVR) and convolutional neural network (CNN) models offer a promising solution for real-time process control due to the models’ abilities to recognize complex, non-linear patterns with high accuracy. A novel experiment was designed to compare the performance of SVR and CNN models to indirectly detect bead height from a coaxial image of a melt pool from a single-layer, single bead build. The study showed that both SVR and CNN models trained on melt pool data collected from a coaxial optical camera can accurately predict the bead height with a mean absolute percentage error of 3.67% and 3.68%, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fluoride Analysis by Ion Chromatography in Support of Fast Critical Assembly (FCA) Spent Nuclear Fuel Processing

INTRODUCTION The Savannah River Site (SRS) is currently processing Fast Critical Assembly (FCA) fuel received from the Japan Atomic Energy Agency (JAEA) for disposition. Stainless steel-clad plate and rods in stainless steel containers are dissolved using electrolysis with a solution mixture of nitric acid (HNO3), potassium fluoride (KF), and gadolinium (Gd). An ion chromatography (IC) was developed and vetted to monitor fluoride at various sampling points of the process. To finalize the method, FCA test solution was analyzed to qualify the analytical method followed by real FCA process solution analysis using two different analytical columns. This presentation summarizes the development and vetting of the IC method.

White, Thomas L. [Savannah River National Laborato↗
DOE OSTI2023

Molecular Insight into the Effects of Clustering on the Dynamics of Ionomers in Solutions

Ionizable groups tethered to polymers enable their many current and potential applications. However, these functionalities drive the formation of physical networks through clustering of the ionic groups, resulting in constrained dynamics of the macromolecules. Understanding the molecular origin of this hindrance remains a critical fundamental question, whose solution will directly impact the processing of ionizable polymers from molecules to viable materials. Here, in this work, using quasielastic neutron scattering accompanied by molecular dynamics simulations, segmental dynamics of slightly sulfonated polystyrene is studied in solutions as the cohesion of the ionic assemblies is tuned. We find that in cyclohexane the ionic assemblies act as centers of confinement, affecting dynamics both on macroscopic lengths and in the vicinity of the ionic assemblies. Addition of a small amount of ethanol affects the packing of the ionizable groups within the assemblies, which in turn enhances the chain dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Production processing and workflow management software evaluation in the DUNE collaboration

The Deep Underground Neutrino Experiment (DUNE) will be theworld’s foremost neutrino detector when it begins taking data in the mid-2020s.Two prototype detectors, collectively known as ProtoDUNE, have begun tak-ing data at CERN and have accumulated over 3 PB of raw and reconstructeddata since September 2018. Particle interaction within liquid argon time projec-tion chambers are challenging to reconstruct, and the collaboration has set upa dedicated Production Processing group to perform centralized reconstructionof the large ProtoDUNE datasets as well as to generate large-scale Monte Carlosimulation. Part of the production infrastructure includes workflow manage-ment software and monitoring tools that are necessary to eciently submit andmonitor the large and diverse set of jobs needed to meet the experiment’s goals.We will give a brief overview of DUNE and ProtoDUNE, describe the varioustypes of jobs within the Production Processing group’s purview, and discuss thesoftware and workflow management strategies are currently in place to meetexisting demand. We will conclude with a description of our requirements in aworkflow management software solution and our planned evaluation process.

Herner, Kenneth R.↗
DOE OSTI2023

Demonstration of Scaled-Production of Rare Earth Oxides and Critical Materials from U. S. Coal-Based Sources (Final Report)

The project objective was to demonstrate scaled production of high purity rare earth oxides (REO), nominally exceeding 90% grade, from coal refuse sources using innovative technologies that reduce cost and improve environmental outcomes relative to traditional rare earth processing technologies. The project utilized a critical material pilot plant constructed and tested as part of a previous U.S. Department of Energy project. Target performance criteria was a 50% reduction in production cost based on previous optimum values, 150% increase in recovery and greater than 2% concentrates of rare earth oxides, cobalt and manganese. Concentrate production goals were to produce a rare earth mix oxide product at a rate of 200 grams per day having a minimum purity of 50% as well as products of cobalt and manganese having a minimum purity of 2%. A previous pilot plant investigation identified acid cost as the major contributor to an operating cost that made the recovery of rare earth and other critical metals from bituminous coal sources economically challenging. As such, acid cost reduction was a major target using bio-oxidation reactors to produce sulfuric acid from naturally occurring coal pyrite. Based on laboratory data, a bio-oxidation circuit was designed for the pilot plant to produce 7.5 l/min of acid using two 11-m3 (3000 gallon) reactors equipped with 40 hp aerators for air dispersion. The pilot-scale tests revealed that acid concentration equivalent to as high as 1.0 M sulfuric acid could be continuously produced. However, the bio-acid contained exceptionally high iron concentrations, which complicated downstream processing of the pregnant leach solution (PLS). A TEA of the bio-oxidation circuit showed that production cost was approximately $0.13 per kg acid equivalent if produced using a four-day retention time in the reactors. This value represents a 48% reduction from that of purchased bulk sulfuric acid. Calcination (or roasting) studies were conducted on coarse refuse from West Kentucky No. 13 and Fire Clay coal seam sources. The test results revealed the potential to increase recovery by nearly 100% using temperatures between 500°C to 700°C with light REE recovery value being the most improved. Acid baking of the calcined products using sulfuric acid at 250°C increased heavy rare earth recovery from around 40% to 80% while decreasing the acid requirements by over 50%. The existing pilot plant was upgraded for the pilot scale demonstration of REE and CM recovery. The primary feedstocks were West Kentucky No.13 and heap leach pregnant leach solution (PLS) while a secondary feedstock was a lignite waste material from a construction sand operation. The pilot scale operation started with PLS generation through leaching followed by iron and aluminum removal, nominally at 3.3 and 4.5 pH, respectively. Leaching lixiviants used for the test were industrial grade sulfuric acid or bio-acid generated at the pilot scale facility. For most of the tests, the solid feed rate was 200 lb/hr whereas lixiviant was added at 2 gpm to provide an optimal residence time of 45 minutes. Following the contaminant removal step, several different process schematics were tested with the goal of maximizing REE recovery and purity. In the first test, direct processing of aluminum precipitation raffinate for REE recovery using oxalic acid at pH 1.5 was investigated. Overall REE recovery was approximately 45%. Unfortunately, elevated calcium content in the PLS significantly impacted the RE-Oxide product grade. Similarly, high calcium content decreased both the product purity and grades of CM products. As such, a new flowsheet was tested with the same initial process schematic but different precipitation stages for REEs and CMs at pH 6.0 and 9.0, respectively. It was noted that the overlapping precipitation behavior of Co, Ni and Zn with REEs limited the applicability of this process schematic. While this change increased the RE-Oxide grade from 36% in the first test to 87%, the loss of critical metals to the REE cake and bypass of the REEs to the CM cake significantly impacted the recovery of both REEs and CMs. Therefore, the modified process flowsheet combined oxalic acid precipitation stage raffinate and redissolved CM cake filtrate to maximize both the recovery and purity of the products. Consequently, a RE-Oxide product with 85% purity and CM cakes with over 19% Co, 38% Ni, 14% Zn and 9% Mn content were generated with significantly higher recoveries. While the modified process flowsheet improved recoveries and grades, elemental losses observed in separate precipitation and redissolution losses inspired the adaptation of a single precipitation stage at pH 9.0 for both REEs and CMs. This change was anticipated to maximize the REE recovery while minimizing the costs associated with separated redissolution and processing stages. As expected, REE recovery in this new circuit arrangement was over 56% with a product grade of over 87% RE-Oxide content. Similarly, Co, Ni, Mn, and Zn recoveries of 54%, 40%, 67%, and 66%, respectively, were achieved. Unfortunately, the elevated calcium content present in the solution due to its precipitation at pH 9.0 caused a decrease in the CM cake quality. Therefore, the final process flowsheet involved the addition of calcium oxalate precipitation following the oxalic acid precipitation stage, which effectively eliminated calcium contamination of the CM products. Finally, the pilot scale experiments conducted using bio-acid achieved comparable REE leaching recoveries to the conventional sulfuric acid leaching. Elevated iron concentration in the solution caused the co-precipitation of REEs with the iron and aluminum cake, resulting in the REE losses. Furthermore, elevated iron content bypassing the iron and aluminum precipitation stages contaminated the metal sulfide and manganese cake, respectively. A techno-economic analysis was performed based on a commercial facility capable of treating 500 tph of coal-based material. The production cost for West Kentucky No. 13 coarse refuse material ranged from approximately $500-$700/kg of total rare earth oxide whereas the lignite source had significantly lower production cost of $100-$300/kg. The significant difference in cost was due to the easier leaching characteristics of the lignite material and the higher feed concentrations. All process scenarios resulted in a negative net present value (NPV). For the lignite feedstock, laboratory REE leach recovery values were about 30% higher than the pilot plant data. Using the lab leach results, a positive net present value was achieved and the production cost decreased from $100-$300 $/kg to less than $150/kg of total REO.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Scalable branching on dual decomposition of stochastic mixed-integer programming problems

In this work, we present a scalable branching method for the dual decomposition of stochastic mixed-integer programming. Our new branching method is based on the branching method proposed by Caroe and Schultz that creates branching disjunctions on first-stage variables only. We propose improvements to the process for creating branching disjunctions, including (1) branching on the optimal solutions of the Dantzig-Wolfe reformulation of the restricted master problem and (2) using a more comprehensive (yet simple) measure for the dispersions associated with subproblem solution infeasibility. We prove that the proposed branching process leads to an algorithm that terminates finitely, and we provide conditions under which globally optimal solutions can be identified after termination. We have implemented our new branching method, as well as the Caroe-Schultz method and a branch-and-price method, in the open-source software package DSP. Using SIPLIB test instances, we present extensive numerical results to demonstrate that the proposed branching method significantly reduces the number of node subproblems and solution times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗