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At least 847 records · Page 47

Graded thermoelectric materials

This disclosure provides systems, methods, and apparatus related to graded thermoelectric materials. In one aspect, a method includes providing a plurality of nanostructures. The plurality of nanostructures comprise a thermoelectric material, with nanostructures of the plurality of nanostructures having first ligands disposed on surfaces of the nanostructures. The plurality of nanostructures is deposited on a substrate to form a layer. The layer is contacted with a solution containing second ligands. A ligand exchange process occurs where some of the first ligands disposed on the plurality of nanostructures are replaced with the second ligands. A first region of the layer is removed from contact with the solution so that the ligand exchange process does not occur in the first region of the layer, with the ligand exchange process occurring in the layer in contact with the solution. The layer is then removed from contact with the solution.

36 MATERIALS SCIENCE↗

Challenges, progress, and future perspectives for cyanobacterial polyhydroxyalkanoate production

Polyhydroxyalkanoates (PHA) are a promising bio-based alternative to traditional plastics derived from petroleum. Cyanobacteria are photosynthetic organisms that produce PHA from CO 2 and sunlight, which can potentially reduce production costs and environmental footprint in comparison to heterotrophic bacteria cultures because (1) they utilize inorganic carbon sources for growth and (2) they do not require intensive aeration for oxygenation. Moreover, supplementing precursors such as propionate, acetate, valerate, etc., can be used to obtain various copolymers with plastic customizable properties in comparison to the classical homopolymers, such as polyhydroxybutyrate, PHB. This critical review covers the latest advances in PHA production, including recent discoveries in the metabolism interplay between PHA and glycogen production, and new insights into cultivation strategies that enhance PHA accumulation, and purification processes. This review also addresses the challenges and suggests potential solutions for a viable industrial PHAs production process.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges, Progress, and Future Perspectives for Cyanobacterial Polyhydroxybutyrate Production

Polyhydroxyalkanoates (PHA) are a promising bio-based alternative to traditional plastics derived from petroleum. Cyanobacteria are photosynthetic organisms that produce PHA from CO 2 and sunlight, which can potentially reduce production costs and environmental footprint in comparison to heterotrophic bacteria cultures because (1) they utilize inorganic carbon sources for growth and (2) they do not require intensive aeration for oxygenation. Moreover, supplementing precursors such as propionate, acetate, valerate, etc., can be used to obtain various copolymers with plastic customizable properties in comparison to the classical homopolymers, such as polyhydroxybutyrate, PHB. This critical review covers the latest advances in PHA production, including recent discoveries in the metabolism interplay between PHA and glycogen production, and new insights into cultivation strategies that enhance PHA accumulation, and purification processes. This review also addresses the challenges and suggests potential solutions for a viable industrial PHAs production process.

60 APPLIED LIFE SCIENCES↗

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗

IDAES-PSE 2.7.0 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 2.7.0 Release Highlights New features: AutoScaler and CustomScalerBase classes: Such tools are the core of the new scaling framework being implemented in IDAES. Wider adoption of scaling tools among users will result in quicker and more robust model solutions. Scaler for equilibrium reactor and saponification properties: These scaler models are examples to follow for how to use the new scaling tools. ONNX Surrogate support from Optimization & Machine Learning Toolkit (OMLT): ONNX is an open standard format to save and load ML/AI models that is widely supported by all major frameworks. This capability makes it easier for IDAES users to create surrogate models and use them without having to support each framework individually. 1D Membrane Model for CO2 Capture and Utilization: Supports ongoing efforts for modeling and optimizing polymer membrane processes for CO2 capture and conversion into formic acid. StreamScaler unit model: Unrelated to the CustomScalerBase, this unit model allows a stream’s extensive variables to be scaled by a fixed factor. This allows streams being processed by multiple units in parallel to be scaled down to unit scale and scaled back up to process scale. Bug fixes or improvements: Scaling, EoS, Diagnostics tool, Modular Properties, tests & documentation Deprecations: Old Cubic EoS

AS↗

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↗

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↗

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↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

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.↗

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↗

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↗