Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Controls library”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

332 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Caldera Infrastructure Charge Module (ICM)

Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as "Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2025

Investigation of design principles for metal-binding and conductive protein assemblies

Throughout the lifetime of this initiative, including renewals, we focused on understanding the fundamental principles of protein-protein interface design that enable predictable and modular spatial and kinetic control of multi-component protein self-assembly in 1D, 2D, and 3D, including the interface with inorganic materials, small molecules, and metal ions. We designed individual protein components that bind specific metal ions, including REEs and transport ions across lipid membranes. We created helical 1D filaments of repeating units with programmed periodicity, pitch, and multi-component environmentally responsive self-assembling protein fibers. We showed that these filaments reversibly assemble and disassemble under specific pH conditions and created end-specific caps that independently tune the balance of attachment and detachment rates at each terminus of the filament. Using similar filaments, we succeeded in binding arrays of heme and chlorophyll molecules and assembling patterned helical coatings around carbon nanotubes in efforts to create de novo conductive nanowires. By arraying REE binding sites in a large circular tandem array with a repeat protein-based cyclic oligomer, we created a molecular scaffold for superradiance and paramagnetic quantum sensing. We created a range of one-component and two-component self-assembling 2D arrays and showed that when designed to engage cell receptors, these arrays can control cell behavior from outside the cell signal to inside the cell. We designed helical repeat proteins with variable lengths displaying charged residues in a pattern matched to the cation lattice of mica. achieved a range of ordered states with an epitaxial match to the underlying crystal lattice. We further applied the learned principles of protein-induced biomineralization to design proteins with an interface lattice matching CaCO 3 and guide the formation of specific crystal forms of CaCO 3 from solution, a significant advance toward the global need to manage carbon. In all cases of mineral lattice matching and biomineralization, we followed assembly using molecularly resolved in situ AFM imaging and extracted information about assembly pathways and energetics, applying deep learning to quantify the dynamics of protein self-organization. We developed techniques for using dynamic metal-dependent interfaces on protein nanopores for discriminatively sensing dilute REEs in solution and demonstrated the use of strong metal-binding interfaces to drive nanocage disassembly for conditional nanocompartmentalization applications. This grant supported 11 people, including Asim Bera, Evans Brackenbrough, Andrew Borst, Nikita Hanikel, Timothy Huddy, Emily Joyce, Alex Young-Seug Kang, Ryan Kibler, Joshua Morris Lubner, Harley Pyles, and Shuai Zhang. The research effort culminated in the production of published papers and theses. Electronic Thesis/Dissertation are distributed by ProQuest/UMI Dissertation Publishing and made available on an open access basis through UW Libraries ResearchWorks Service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Effect of Charged Block Length Mismatch on Double Diblock Polyelectrolyte Complex Micelle Cores

Polyelectrolyte complex micelles are hydrophilic nanoparticles that self-assemble in aqueous environments due to associative microphase separation between oppositely charged blocky polyelectrolytes. In this work, we employ a suite of physical characterization tools to examine the effect of charged block length mismatch on the equilibrium structure of double diblock polyelectrolyte complex micelles (D-PCMs) by mixing a diverse library of peptide and synthetic charged-neutral block polyelectrolytes with a wide range of charged block lengths (25–200 units) and chemistries. Early work on D-PCMs suggested that this class of micelles can only be formed from blocky polyelectrolytes with identical charged block lengths, a phenomenon referred to as chain length recognition. Here, we use salt annealing to create PCMs at equilibrium, which shows that chain length recognition, a longstanding hurdle to repeatable self-assembly from mismatched polyelectrolytes, can be overcome. Interestingly, D-PCM structure–property relationships display a range of values that vary systematically with the charged block lengths and chemical identity of constituent polyelectrolyte pairings and cannot be described by generalizable scaling laws. We discuss the interdependent growth behavior of the radius, ionic pair aggregation number, and density in the micelle core for three chemically distinct diblock pairings and suggest a potential physical mechanism that leads to this unique behavior. By comparing the results of these D-PCMs to the scaling laws recently developed for single diblock polyelectrolyte complex micelles (S-PCMs: diblock + homopolymer), we observe that D-PCM design schemes reduce the size and aggregation number and restrict their growth to a function of charged block length relative to S-PCMs. Understanding these favorable attributes enables more predictive use of a wider array of charged molecular building blocks to anticipate and control macroscopic properties of micelles spanning countless storage and delivery applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling and Simulation of Fuel Burnup in Pebble Bed Reactors

Modeling and simulation of fuel burnup plays important roles in reactor design, operation, safety, and security as well as nuclear material control and accounting (MC&A) [1]. This task is uniquely challenging for pebble bed reactors (PBR) because the pebbles are continuously added and recycled into the reactor core, and their paths through the core are random. To address this problem, we present two simulation models in this paper. Brookhaven National Laboratory (BNL) developed a simple lattice model of a PBR in Serpent software to generate used pebble isotopic concentrations. The benefit of using Serpent software in this specific application is that it helps streamline the data generation process without having to use too many independent software codes in combination to achieve a simple task. For example, transport, burnup and zero power decay can be implemented in a single pass. Three-dimensional core models were developed using Serpent to simulate the burnup process of 5 subject pebbles starting from fresh till they reach nearly target burnup, with each pebble placed in one of the five artificially designated radial channels to capture the changing neutron spectra along the core radius. Equilibrium isotopic concentrations were assumed in all other pebbles in the core. To provide a verification for the Serpent isotope transmutation and decay results, Oak Ridge National Laboratory (ORNL) performed simple SCALE/ORIGEN calculations using the average neutron spectra calculated by Serpent for each of the 5 pebbles. The 252-group neutron spectra from Serpent were then used by ORIGEN to produce the one-group library for depletion and decay calculations. The isotopic concentrations of a few nuclides of interest and neutron and gamma source terms produced from the ORIGEN calculations were compared with the ones from the Serpent calculations. The model simulated in this work was based on the Pebble Bed Modular Reactor (PBMR)-400 design because many data needed for the simulation such as core power profiles, fuel and reflector temperatures, and equilibrium core composition are publicly available. In this paper, we will compare the results between these two approaches and benchmark the results against a set of well-established simulation results for PBMR-400.

Dim, Odera↗
DOE OSTI2023

Modeling and Simulation of Fuel Burnup in Pebble Bed Reactors

Modeling and simulation of fuel burnup plays important roles in reactor design, operation, safety, and security as well as nuclear material control and accounting (MC&A) [1]. This task is uniquely challenging for pebble bed reactors (PBR) because the pebbles are continuously added and recycled into the reactor core, and their paths through the core are random. To address this problem, we present two simulation models in this paper. Brookhaven National Laboratory (BNL) developed a simple lattice model of a PBR in Serpent software to generate used pebble isotopic concentrations. The benefit of using Serpent software in this specific application is that it helps streamline the data generation process without having to use too many independent software codes in combination to achieve a simple task. For example, transport, burnup and zero power decay can be implemented in a single pass. Three-dimensional core models were developed using Serpent to simulate the burnup process of five subject pebbles starting from fresh till they reach nearly target burnup, with each pebble placed in one of the five artificially designated radial channels to capture the changing neutron spectra along the core radius. Equilibrium isotopic concentrations were assumed in all other pebbles in the core. To provide a verification for the Serpent isotope transmutation and decay results, Oak Ridge National Laboratory (ORNL) performed simple SCALE/ORIGEN calculations using the average neutron spectra calculated by Serpent for each of the five pebbles. The 252-group neutron spectra from Serpent were then used by ORIGEN to produce the one-group library for depletion and decay calculations. The isotopic concentrations of a few nuclides of interest and neutron and gamma source terms produced from the ORIGEN calculations were compared with the ones from the Serpent calculations. The model simulated in this work was based on the Pebble Bed Modular Reactor (PBMR)-400 design because many data needed for the simulation such as core power profiles, fuel and reflector temperatures, and equilibrium core composition are publicly available. In this paper, we will compare the results between these two approaches and benchmark the results against a set of well-established simulation results for PBMR-400.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Engineering Nanostructured Interfaces of Hexagonal Boron Nitride-Based Materials for Enhanced Catalysis

Hexagonal boron nitrides (h-BNs) are attractive two-dimensional (2D) nanomaterials that consist of alternating B and N atoms and layered honeycomb-like structures similar to graphene. They have exhibited unique properties and promising application potentials in the field of energy storage and transformation. Recent advances in utilizing h-BN as a metal-free catalyst in the oxidative dehydrogenation of propane have triggered broad interests in exploring h-BN in catalysis. However, h-BN-based materials as robust nanocatalysts in heterogeneous catalysis are still underexplored because of the limited methodologies capable of affording h-BN with controllable crystallinity, abundant porosity, high purity, and defect engineering, which played important roles in tuning their catalytic performance. Here, in this account, our recent progress in addressing the above issues will be highlighted, including the synthesis of high-quality h-BN-based nanomaterials via both bottom-up and top-down pathways and their catalytic utilization as metal-free catalysts or as supports to tune the interfacial electronic properties on the metal nanoparticles (NPs). First, we will focus on the large-scale fabrication of h-BN nanosheets (h-BNNSs) with high crystallinity, improved surface area, satisfactory purity, and tunable defects. h-BN derived from the traditional approaches using boron trioxide and urea as the starting materials generally contains carbon/oxygen impurities and has low crystallinity. Several new strategies were developed to address the issues. Using bulk h-BN as the precursor via gas exfoliation in liquid nitrogen, single- or few-layered h-BNNS with abundant defects could be generated. Amorphous h-BN precursors could be converted to h-BN nanosheets with high crystallinity assisted by a magnesium metallic flux via a successive dissolution/precipitation/crystallization procedure. The as-fabricated h-BNNS featured high crystallinity and purity as well as abundant porosity. An ionothermal metathesis procedure was developed using inorganic molten salts (NaNH 2 and NaBH 4 ) as the precursors. The h-BN scaffolds could be produced on a large scale with high yield, and the as-afforded materials possessed high purity and crystallinity. Second, utilization of the as-prepared h-BN library as metal-free catalysts in dehydrogenation and hydrogenation reactions will be summarized, in which they exhibited enhanced catalytic activity over the counterparts from the previous synthesis method. Third, the interface modulation between metal NPs with the as-prepared defects’ abundant h-BN support will be highlighted. The h-BN-based strong metal–support interaction (SMSI) nanocatalysts were constructed without involving reducible metal oxides via the ionothermal procedure we developed by deploying specific inorganic metal salts, acting as robust nanocatalysts in CO oxidation. Under conditions simulated for practical exhaust systems, promising catalytic efficiency together with high thermal stability and sintering resistance was achieved. Across all of these examples, unique insights into structures, defects, and interfaces that emerge from in-depth characterization through microscopy, spectroscopy, and diffraction will be highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

IDAES-PSE 2.5.0 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, most environmentally sustainable 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 2.5.0 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 diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. 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. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗
DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗