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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 253 records · Page 14

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗

Scalable nanomanufacturing of chalcogenide inks: a case study on thermoelectric V–VI nanoplates

Solution-processed semiconducting main-group chalcogenides (MMCs) have attracted increasing research interest for next-generation device technologies owing to their unique nanostructures and superior properties. To achieve the full potential of MMCs, the development of highly universal, scalable, and sustainable synthesis and processing methods of chalcogenide particles is thus becoming progressively more important. Here we studied scalable factors for the synthesis of two-dimensional (2D) V–VI chalcogenide nanoplates (M 2 Q 3 : M = Sb, Bi; Q = Se, Te) and systematically investigated their colloidal behaviour and chemical stability. Based on a solvent engineering technique, we demonstrated scale-up syntheses of MMCs up to a 900% increase of batch size compared with conventional hydrazine-based gram-level syntheses, and such a scalable approach is highly applicable to various binary and ternary MMCs. Furthermore, we studied the stability of printable chalcogenide nanoparticle inks with several formulation factors including solvents, additives, and pH values, resulting in inks with high chemical stability (>4 months). As a proof of concept, we applied our solution-processed chalcogenide particles to multiple additive manufacturing methods, confirming the high printability and processability of MMC inks. Furthermore, the ability to combine the top-down designing freedom of additive manufacturing with bottom-up scalable synthesis of chalcogenide particles promises great opportunities for large-scale design and manufacturing of chalcogenide-based functional devices for broad application.

36 MATERIALS SCIENCE↗

A domain decomposition preconditioning for an inverse volume scattering problem

In this work, we propose domain decomposition preconditioners for the solution of an integral equation formulation of the acoustic forward and inverse scattering problems. We study both forward and inverse volume problems and propose preconditioning techniques to accelerate the iterative solvers. For the forward scattering problem, we extend the domain decomposition based preconditioning techniques presented for partial differential equations in Cai and Sarkis (1999 SIAM J. Sci. Comput. 21 792–797), to integral equations. We combine this domain decomposition preconditioner with a low-rank correction, which is easy to construct, forming a new preconditioner. For the inverse scattering problem, we use the forward problem preconditioner as a building block for constructing a preconditioner for the Gauss–Newton Hessian. We present numerical results that demonstrate the performance of both preconditioning strategies.

97 MATHEMATICS AND COMPUTING↗

Physical and Flow Properties of Glass Forming Chemicals (V2O5, SnO, SnO2, Cr2O3, FeCr2O4, and ZrSiO4) and Mixtures

For a sustainable nuclear waste vitrification process at the Hanford Tank Waste Treatment and Immobilization Plant (WTP), proper selection and consistent supply of glass-forming chemicals (GFCs) are crucial. Establishing rigorous acceptance criteria for the characterization of GFCs will be required to operate the vitrification facility and to mitigate any processing issues or failures. Low-activity wastes (LAW) are blended with GFCs to form slurry melter feeds and vitrified in a melter. To enhance properties of waste glasses, new chemicals are being introduced to the current GFC mixture (Vienna et al. 2016; Muller et al. 2017, 2019). In this study, three new GFCs were evaluated for enhanced LAW glass formulations: chromium oxide (Cr 2 O 3 ), vanadium oxide (V 2 O 5 ), and stannic oxide (SnO 2 ). These three oxide components are included in enhanced waste glass (EWG) formulations and GFCs with the appropriate physical and flow properties are needed. As a starting point, single metal oxide GFCs: Cr 2 O 3 , V 2 O 5 , and SnO 2 were sourced and tested. To characterize these new individual GFCs and mixtures of GFCs, the industrial bulk characterization consultant, Jenike and Johanson, was employed to measure physical and flow properties of individual GFCs and their mixtures. Pacific Northwest National Laboratory (PNNL) also measured several selected physical properties for data evaluation as a quality assurance step. In addition, PNNL measured physical and rheological properties of slurry melter feeds containing those GFCs. Subsequent data analyses and verification were conducted. The purpose of this report is to assess the applicability of these GFCs for LAW vitrification based on their properties. This report will help understand measured data and evaluate new GFCs for use. Moreover, this report may give useful insights to help troubleshoot any GFC and melter feed transport and mixing issues that arise during processing, leading to a successful cleanup mission at WTP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Physical and Flow Properties of Glass-Forming Chemicals (V 2 O 5 , SnO, SnO 2 , Cr 2 O 3 , FeCr 2 O 4 , and ZrSiO 4 ) and Mixtures

For an efficient nuclear waste vitrification process at the Waste Treatment and Immobilization Plant (WTP) on the Hanford Site, proper selection and consistent supply of glass-forming chemicals (GFCs) are crucial. Thorough characterization of the GFCs is required to reduce risks in operation of the vitrification facility. Low-activity waste (LAW) will be blended with GFCs to form slurry feeds and then fed to melters and vitrified. To enhance properties of waste glasses, new chemicals are being introduced to the current GFC mixture. In this study, three new GFCs were evaluated for enhanced LAW glass formulations: chromium oxide (Cr 2 O 3 ), vanadium oxide (V 2 O 5 ), and stannic oxide (SnO 2 ). These three oxide components are included in enhanced waste glass formulations, and GFCs with the appropriate physical and flow properties are needed. As a starting point, single metal oxide GFCs, Cr 2 O 3 , V 2 O 5 , and SnO 2 , were sourced and tested. Then, alternative sources of Sn and Cr (SnO and FeCr 2 O 4 ) were tested along with an alternative zircon source (ZrSiO 4 ). This report documents the work performed to collect physical and flow property data on these new GFCs and melter feed slurries generated using these GFCs and simulated low-activity wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gas-phase stability of large lanthanide:diglycolamide clusters evaluated using collision-induced dissociation

Efficient utilization of long-term deep geologic storage repositories is critical for the large-scale deployment of nuclear energy. As the minor actinides (americium and curium) are the largest contributor to the decay heat of used nuclear fuel after a few hundred years, their removal from used fuel prior to disposal can significantly increase the amount of waste that can be stored in a given volume. The development of ligands that can effectively separate the minor actinides from other components of used nuclear fuel are crucial to efficient utilization of geological storage repositories. N,N,N’,N’-tetraoctyl diglycolamide (TODGA) is a promising extractant for the separation of lanthanides and the minor actinides from other components of used nuclear fuel. While the use of TODGA in f-element separations has been investigated in process-based formulations, gas-phase metal ion cluster experiments enable the study of covalent interactions in reprocessing systems absent from solvent effects. Exploring fundamental differences in lanthanide-ligand covalent interactions can impact the development and implementation of actinide-lanthanide separation systems in nuclear fuels reprocessing. In this study, lanthanide-TODGA clusters were synthesized in the gas-phase and identified using mass spectrometry fragmentation experiments. Large europium and samarium clusters were identified that contained up to 8 and 10 bound TODGA ligands, respectively; this was surprising due to the size and multidentate binding that is normal for TODGA. In addition, while smaller clusters showed evidence of sequential ligand fragmentation, larger clusters displayed the loss of neutral TODGA with applied collision voltage. Interestingly, the voltage required for this removal decreased as more TODGA ligands were bound to the metal, suggesting that the metal coordination sphere was becoming more saturated and TODGA ligands were more weakly bound as the clusters got larger.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Improving the Physical Basis for Updraft Dynamics in Deep Convection Parameterizations

This article presents a new deep convective parameterization that determines cloud characteristics based on a specified cloud size distribution. The vertical profiles of cloud properties are determined by analytic equations, which formulate entrainment with an inverse relationship to cloud width. In line with recent studies of large eddy simulations (LES), cloud widths are assumed to be constant with height and vertical mass flux (M) characteristics of the clouds are therefore regulated by the vertical velocity profile. The parameterization is configured to work with existing cloud base M closure formulations, with the closure predicting the total cloud area rather than the cloud base M directly. Analytic formula are also used to connect the vertical wind shear magnitude to the cloud size distribution, wherein larger shear magnitudes result in more numerous large updrafts than weaker shear magnitudes, which is in line with recent research results. The parameterization is compared against 10 deep convective LES with varying thermodynamic and vertical wind shear profiles. Results show dramatic improvements in the prediction of normalized M, detrainment, and the properties of detrained air over the existing Zhang and McFarlane (1995) scheme. In particular, the new model is able to correctly portray the transition from a bottom-heavy M profile in weakly sheared environments, to a top-heavy M profile in strongly sheared environments.

54 ENVIRONMENTAL SCIENCES↗

Benchmarking Cylindrical Blast Wave Theory Against the OSIRIS-REx Sample Return Capsule Reentry

Weak shock theory based on cylindrical blast waves has been used to interpret meteor infrasound, but it has not been systematically benchmarked against a non-ablating hypersonic source with independently known parameters. The objective of this study is not to propose a new theoretical framework, but to evaluate the operational validity of the existing suite of blast radius formulations against a high-fidelity ground truth dataset. The OSIRIS-REx Sample Return Capsule reentry on 24 September 2023 provides such a benchmark because the capsule geometry, trajectory, and infrasound emission points are constrained from mission data and ray tracing, reducing source-side uncertainty associated with ablation. Using observations from 39 infrasound stations, this benchmarking study evaluates six published blast radius (${R}_{0}$ ) formulations and three weak-shock transition coefficients ( C ) within a stratified atmospheric propagation model to predict signal period and peak overpressure. The benchmarking identifies the Sakurai formulation as the best-performing formulation for non-ablating bodies, with the Jones/Plooster formulation performing comparably when a physically appropriate C is adopted. Sakurai and Jones/Plooster yield linear-period median absolute percentage residuals of 9% and 11%, respectively. The period predictions show only weak sensitivity to C at these propagation distances. The Mach-diameter approximation commonly used in meteor studies overestimates ${R}_{0}$ by more than a factor of 3 in the absence of ablation. Finally, these results establish a performance baseline for applying cylindrical blast wave theory to effectively non-ablating hypersonic bodies and demonstrate that the signal period is a robust observable for constraining ${R}_{0}$.

atmospheric entry↗

Development of a Printable Prill Formulation Technique and Demonstration of Monomodal Prill Size on Compaction Density and Compressive Strength

Polymer-bonded explosive molding powder, or “prills,” are relied on for the fabrication of pressed high explosives since the 1950's. The wet granulation technique, also known as “slurry coating,” that is used to formulate prills, is a complex process that results in polydisperse and variable yields. This makes it difficult to study the mesoscale effect that prills have on the microstructure of a pressed article. The following study introduces a novel approach to energetic granulation that leverages techniques used in the additive manufacturing of paste-like energetic materials. This extrusion granulation, or prill printing technique, makes it possible to tailor the sizes and shapes of prills, allowing for their morphological influences to be studied in a controlled manner. The following work details the fabrication and characterization of four monomodal size lots of prills using an inert formulation (95 wt.% melamine, 5 wt.% polymer binder). Prills from each size lot were die-pressed using a fixed recipe to investigate how prill size impacts compaction density and therefore compressive strength. It was found that larger prills influence the pressing density by creating larger defects within the microstructure of a pressed article, resulting in a decrease in compressive strength.

direct ink write↗

Data-driven optimization of mixed-integer bi-level multi-follower integrated planning and scheduling problems under demand uncertainty

The coordination of interconnected elements across the different layers of the supply chain is essential for all industrial processes and the key to optimal decision-making. Yet, the modeling and optimization of such interdependent systems are still burdensome. Here we address the simultaneous modeling and optimization of medium-term planning and short-term scheduling problems under demand uncertainty using mixed-integer bi-level multi-follower programming and data-driven optimization. Bi-level multi-follower programs model the natural hierarchy between different layers of supply chain management holistically, while scenario analysis and data-driven optimization allow us to retrieve the guaranteed feasible solutions of the integrated formulation under various demand considerations. We address the data-driven optimization of this challenging class of problems using the DOMINO framework, which was initially developed to solve single-leader single-follower bi-level optimization problems to guaranteed feasibility. This framework is extended to solve single-leader multi-follower stochastic formulations and its performance is characterized by well-known single and multi-product process scheduling case studies. Through our data-driven algorithmic approach, we present guaranteed feasible solutions to linear and nonlinear mixed-integer bi-level formulations of simultaneous planning and scheduling problems and further characterize the effects of the scheduling level complexity on the solution performance, which spans over several hundred continuous and binary variables, and thousands of constraints.

42 ENGINEERING↗

Subtle changes in hydrogen bond orientation result in glassification of carbon capture solvents

Water-lean CO 2 capture solvents show promise for more efficient and cost-effective CO 2 capture, although their long-term behavior in operation has yet to be well studied. New observations of extended structure solvent behavior show that some solvent formulations transform into a glass-like phase upon aging at operating temperatures after contact with CO 2 . The glassification of a solvent would be detrimental to a carbon-capture process due to plugging of infrastructure, introducing a critical need to decipher the underlying principles of this phenomenon to prevent it from happening. In this work, we present the first integrated theoretical and experimental study to characterize the nano-structure of metastable and glassy states of an archetypal single-component alkanolguanidine carbon-capture solvent and assess how minute changes in atomic-level interactions convert the solvent between metastable and glass-like states. Small-angle neutron scattering and neutron diffraction coupled with small- and wide-angle X-ray scattering analysis demonstrate that minute structural changes in solution precipitae reversible aggregation of zwitterionic alkylcarbonate clusters in solution. Our findings indicate that our test system, an alkanolguanidine, exhibits a first-order phase transition, similar to a glass transition, at approximately 40 °C—close to the operating absorption temperature for post-combustion CO 2 capture processes. We anticipate that these phenomena are not specific to this system, but are present in other classes of colvents as well. We discuss how molecular-level interactions can have vast implications for solvent-based carbon-capture technologies, concluding that fortunately in this case, glassification of water-lean solvents can be avoided as long as the solvent is run above its glass transition temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Extending evolutionary forecasts across bacterial species

Improving evolutionary forecasting requires progressing from studying repeated evolution of a single genotype under identical conditions to formulating broad principles. These principles should enable predictions of how similar species will adapt to similar selective pressures. Evolve-and-resequence experiments with multiple species allow testing forecasts on different biological levels and elucidating the causes for failed predictions. Here, we show that forecasts for adaptation to static culture conditions can be extended to multiple species by testing previous predictions for Pseudomonas syringae and Pseudomonas savastanoi. In addition to sequence divergence, these species differ in their repertoire of biofilm regulatory genes and structural components. Consistent with predictions, both species repeatedly produced biofilm mutants with a wrinkly spreader phenotype. Predominantly, mutations occurred in the wsp operon, with less frequent promoter mutations near uncharacterized diguanylate cyclases. However, mutational patterns differed on the gene level, which was explained by a lack of conservation in relative fitness of mutants between more divergent species. The same mutation was the most frequent for both species suggesting that conserved mutation hotspots can increase parallel evolution. This study shows that evolutionary forecasts can be extended across species, but that differences in the genotype–phenotype–fitness map and mutational biases limit predictability on a detailed molecular level.

59 BASIC BIOLOGICAL SCIENCES↗

Comment on “Review of experimental studies of secondary ice production” by Korolev and Leisner (2020)

Abstract. This is a comment on the review by Korolev and Leisner (2020, hereafter KL2020). The only two laboratory/field studies ever to measure the breakup in ice–ice collisions for in-cloud conditions were negatively criticised by KL2020, as were our subsequent theoretical and modelling studies informed by both studies. First, hypothetically, even without any further laboratory experiments, such theoretical and modelling studies would continue to be possible, based on classical mechanics and statistical physics. They are not sensitive to the accuracy of lab data for typical situations, partly because the nonlinear explosive growth of ice concentrations continues until some maximum concentration is reached. To a degree, the same final concentration is expected regardless of the fragment number per collision. Second, there is no evidence that both lab/field observational studies characterising fragmentation in ice–ice collisions are either mutually conflicting or erroneous such that they cannot be used to represent this breakup in numerical models, contrary to the review. The fact that the ice spheres of one experiment were hail sized (2 cm) is not a problem if a universal theoretical formulation, such as ours, with fundamental dependencies, is informed by it. Although both lab/field studies involved head-on collisions, rotational kinetic energy for all collisions generally is only a small fraction of the initial collision kinetic energy (CKE) anyway. Although both lab/field experiments involved fixed targets, that is not a problem since the fixing of the target is represented via CKE in any energy-based formulation such as ours. Finally, scaling analysis suggests that the breakup of ice during sublimation can make a significant contribution to ice enhancement in clouds, again contrary to the impression given by the review.

54 ENVIRONMENTAL SCIENCES↗

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The interesting properties of natural gas as well as the growing electric power demand worldwide have led to increasing attention to natural-gas-based distributed generation applications in electric distribution systems. This paper goes over the interdependency between a residential natural gas network and an electric distribution network that are coupled via fuel cells. The modeling of the gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the gas and electric distribution networks, subject to their model constraints. In addition to this, in order to capture the probabilistic nature of the optimization problem under study, the K-means clustering algorithm is applied to the gas and electricity demands to determine hourly load states and their corresponding probabilities. Furthermore, simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution feeder and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗

Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids

This paper presents a methodology for generating restoration sequences in distribution systems and microgrids with emphasis on deriving optimal switching times for remote control switches (RCS). Microgrid architecture considered are assumed to be operating in islanded single master mode. Control methods for handling the unbalance inherent in distribution systems using single-phase controlled PQ inverters were developed and incorporated in the proposed method. The problem of considering simultaneously both energy optimization and dynamic stability of the system, which is lacking in existing methods, was addressed by studying the transient behavior of microgrids based on extended EMTP simulations and then approximate and incorporate these behaviors into the optimization formulation for restoration. The approach is based on multi-objective optimization of final restored load and total restoration time. The methodology was studied on a modified IEEE 123 node test feeder. An EMTP simulation in PSCAD of the formed microgrids was used to validate the accuracy of the dynamic and steady-state characteristics of the resulting systems. By considering the transient behavior of DGs during restoration, a better restoration sequence that does not trigger protection relays could be realized.

42 ENGINEERING↗

Inkjet printing of epitaxially connected nanocrystal superlattices

Access to a blossoming library of colloidal nanomaterials provides building blocks for complex assembled materials. The journey to bring these prospects to fruition stands to benefit from the application of advanced processing methods. Epitaxially connected nanocrystal (or quantum dot) superlattices present a captivating model system for mesocrystals with intriguing emergent properties. The conventional processing approach to creating these materials involves assembling and attaching the constituent nanocrystals at the interface between two immiscible fluids. Processing small liquid volumes of the colloidal nanocrystal solution involves several complexities arising from the concurrent spreading, evaporation, assembly, and attachment. The ability of inkjet printers to deliver small (typically picoliter) liquid volumes with precise positioning is attractive to advance fundamental insights into the processing science, and thereby potentially enable new routes to incorporate the epitaxially connected superlattices into technology platforms. In this study, we identified the processing window of opportunity, including nanocrystal ink formulation and printing approach to enable delivery of colloidal nanocrystals from an inkjet nozzle onto the surface of a sessile droplet of the immiscible subphase. We demonstrate how inkjet printing can be scaled-down to enable the fabrication of epitaxially connected superlattices on patterned sub-millimeter droplets. Furthermore, we anticipate that insights from this work will spur on future advances to enable more mechanistic insights into the assembly processes and new avenues to create high-fidelity superlattices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Incorporating PCM-enabled thermal energy storage into 3D printable cementitious composites

This paper delineates the feasibility of incorporating microencapsulated phase change materials (mPCM) into 3D printable cementitious composite materials. A comprehensive experimental program was carried out to evaluate the impacts of mPCM on the printability, microstructures, mechanical and thermal properties of cementitious 3D printing ‘inks’. Results showed that the mPCM affected the printability of the cementitious ink material based on its physical properties (e.g., particle size) and volume loading – at lower volume loadings, mPCM increased the flowability of the cementitious ink material while leading to increased compressive strength and thermal conductivity for the hardened printed material. However, further increase in mPCM dosage led to a decrease in printability and, therefore, decrease in compressive strength and thermal conductivity as compared to the reference mixture. Here the results also showed that the inclusion of mPCM influence the printing parameters. In general, the inclusion of higher volume contents of mPCM necessitates a higher extrusion rate to achieve a desirable extrudability. Lastly, a thermal network model was formulated for 3D printed mPCM charged building components (e.g., wall). The study shows that microencapsulated PCM materials have good potential to be used in 3D printable cementitious mixtures for improving the thermal and energy performance of 3D printed buildings.

36 MATERIALS SCIENCE↗