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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Machine-learning-assisted high-temperature reservoir thermal energy storage optimization

High-temperature reservoir thermal energy storage (HT-RTES) has the potential to become an indispensable component in achieving the goal of the net-zero carbon economy, given its capability to balance the intermittent nature of renewable energy generation. In this study, a machine-learning-assisted computational framework is presented to co-optimize the performance metrics of HT-RTES by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Further, neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Pumping Optimization Model for Pump and Treat Systems - 15091

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.

Baker, S.↗
DOE OSTI2022

Hybrid Particle Swarm-Interpolation Algorithm for Improved Critical Experiment Design

The typical goal of designing a critical experiment is twofold: a system that is both critical and optimized for some other value. This value could be an energy-integrated sensitivity, percent fissions in a certain energy range, or some other value that can be calculated by a transport code. By simulating different combinations of reflector, moderator, and fuel thicknesses a designer can identify such a desirable configuration. The domain of all possible combinations of these thicknesses is referred to as the experiment search space. As more dimensions are added, the search space increases in size exponentially. For a three-dimensional case, which includes three thickness values between zero and ten centimeters to the nearest tenth of a millimeter, a total of 1,000 3 , configurations exists. Rather than check each configuration individually, which would be extremely computationally expensive, it has been shown to be more efficient to use a conventional particle swarm optimization (PSO) algorithm to identify critical and optimal configurations. This work presents the theory and implementation of a novel hybrid PSO interpolation algorithm to perform these optimizations faster than a conventional PSO algorithm. To demonstrate this, an example optimization will be carried out by the conventional and hybrid PSO algorithms and their performances will be compared.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

High Performance Solution for Security Constrained Optimal Power Flow

Solving the Alternating Current Optimal Power Flow (ACOPF) problem is key to economically efficient and reliable power networks with a good solution potentially saving utilities tens of billions of dollars annually (according to FERC). The Grid Optimization (GO) Competition set up by ARPA-E saw several promising solutions in Challenge 1. While team GOT-TJU-OPF placed top 10 in Division 3 and 4, this was not a satisfactory performance, and the team has identified specific areas to improve and will be adding more members to round out the necessary skills and expertise needed to be more competitive. The team set out for redemption during GO Challenge 2 with an improved High-Performance Solution for Security Constrained Optimal Power Flow. The (renamed) BSI-GOT-OPF Team ended up finishing top 2 overall in the competition. The algorithms developed have potential impacts for the electric power markets that are enormous. Optimal Power Flow technology can be an enabling technology to achieve energy-efficient power grids while enhancing renewable energy penetration, among others.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Aero-structural design and optimization of 50 MW wind turbine with over 250-m blades

The quest for reduced levelized cost of energy has driven significant growth in wind turbine size; however, larger rotors face significant technical and logistical challenges. The largest published rotor design is 25 MW, and here we consider an even larger 50 MW design with blade length over 250 m. This paper shows that a 50 MW design is indeed possible from a detailed engineering perspective and presents a series of aero-structural blade designs, and critical assessment of technology pathways and challenges for extreme-scale rotors. The 50 MW rotor design begins with Monte Carlo simulations focused on optimizing carbon spar cap and root design. A baseline design resulted in a 250-m blade with mass of 502 tonnes. Subsequently, an aero-structural design and optimization were performed to reduce the blade mass/cost with more than 25% mass reduction and 30% cost reduction by determining optimal blade chord and airfoil thickness for best aero-structural performance.

Yao, Shulong↗
DOE OSTI2020

Initial conceptual demonstration of control co-design for WEC optimization

Abstract While some engineering fields have benefited from systematic design optimization studies, wave energy converters have yet to successfully incorporate such analyses into practical engineering workflows. The current iterative approach to wave energy converter design leads to sub-optimal solutions. This short paper presents an open-source MATLAB toolbox for performing design optimization studies on wave energy converters where power take-off behavior and realistic constraints can be easily included. This tool incorporates an adaptable control co-design approach, in that a constrained optimal controller is used to simulate device dynamics and populate an arbitrary objective function of the user’s choosing. A brief explanation of the tool’s structure and underlying theory is presented. To demonstrate the capabilities of the tool, verify its functionality, and begin to explore some basic wave energy converter design relationships, three conceptual case studies are presented. In particular, the importance of considering (and constraining) the magnitudes of device motion and forces in design optimization is shown.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Coupling of multiscale imaging analysis and computational modeling for understanding thick cathode degradation mechanisms

Here, using a thick NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) electrode as an example, we present a macro- to nanoscale 2D and 3D imaging analysis approach coupled with 4D (space + time) computational modeling to probe its degradation mechanism in a lithium-ion battery cell. Particle cracking increases and contact loss between particles and carbon-binder domain are observed to correlate with the cell degradation. This study unravels that the reaction heterogeneity within the thick cathode caused by the unbalanced electron conduction is the main cause of the battery degradation over cycling. The increased heterogeneity in the system will entail more cathode regions where the degree of active material utilization is uneven, leading to higher probabilities of particle cracking. These findings shed light on the crucial role of the electronic and ionic transportation networks in the performance deterioration of the thick cathode. They also provide guidance for cathode architecture optimization and performance improvement.

25 ENERGY STORAGE↗
DOE OSTI2020

Controlled Dy-doping to nickel-rich cathode materials in high temperature aerosol synthesis

Layered nickel-rich materials are promising next-generation cathode materials for lithium ion batteries due to their high capacity and low cost. However, the poor thermal stability and longtime cycling performance hinders the commercial applications of high nickel materials. Doping with heteroatoms has been an effective approach for improving electrochemical performance of cathode materials. Controlling doping concentration and geometrical distribution is desired for optimal electrochemical performance, but it is challenging in traditional co-precipitation methods. In this work, controlled dysprosium (Dy) doping to NCM811 was studied in an aerosol synthesis method by controlling the precursor concentrations and heating parameters. The obtained materials were characterized by SEM, XRD, and XPS, and their electrochemical properties and thermal stability were evaluated. By controlling the doping concentration (1.5%), Dy-doped NCM811 was improved simultaneously in long-term cycling and high-rate performance. Here, the thermal-chemical stability of the Dy-doped cathode materials was examined in a microflow reactor with a mass spectrometer. The results showed that Dy-doping shifted the O 2 onset temperature to a higher temperature and reduced O 2 release by 80%, thus dramatically increasing the thermal-chemical stability and improving the fire safety of cathode materials. Since high temperature aerosol synthesis is a low-cost and scalable method, the findings in this work have broad implications for commercial synthesis of novel materials with controlled doping modification to achieve high electrochemical performance and safety in lithium ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2017

Method for computationally efficient design of dielectric laser accelerator structures

Here, dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of only two full-field electromagnetic simulations, the original and ‘adjoint’. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗
DOE OSTI2017

In Silico Design of DNP Polarizing Agents: Can Current Dinitroxides Be Improved?

Numerical calculations of enhancement factors offered by dynamic nuclear polarization in solids under magic angle spinning (DNP-MAS) were performed to determine the optimal EPR parameters for a dinitroxide polarizing agent. We found that the DNP performance of a biradical is more tolerant to the relative orientation of the two nitroxide moieties than previously thought. In general, any condition in which the gyy tensor components of both radicals are perpendicular to one another is expected to have near-optimal DNP performance. These results highlight the important role of the exchange coupling, which can lessen the sensitivity of DNP performance to the inter-radical distance, but also lead to lower enhancements when the number of atoms in the linker becomes less than three. Finally, the calculations showed that the electron T1e value should be near 500μs to yield optimal performance. Importantly, the newest polarizing agents already feature all of the qualities of the optimal polarizing agent, leaving little room for further improvement. Further research into DNP polarizing agents should then target non-nitroxide radicals, as well as improvements in sample formulations to advance high-temperature DNP and limit quenching and reactivity.

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

Quantum optimal control of multiple weakly interacting molecular rotors in the time-dependent Hartree approximation

In this work we perform quantum optimal control simulations, based on the Time-Dependent Hartree (TDH) approximation, for systems of three to five dipole-dipole coupled OCS rotors. A control electric field is used to steer all of the individual rotors, arranged in chains and regular polygons in a plane, toward either identical or unique objectives. The goal is to explore the utility of the TDH approximation to model the field-induced dynamics of multiple interacting rotors in the weak dipole-dipole coupling regime. A stochastic hill climbing approach is employed to seek an optimal control field that achieves the desired objectives at a specified target time. We first show that multiple rotors in chain and polygon geometries can be identically oriented in the same direction; these cases do not significantly depend on the presence of the dipole-dipole interaction. Additionally, in particular geometrical arrangements, we demonstrate that individual rotors can be uniquely manipulated toward different objectives with the same field. Specifically, it is shown that for a three rotor chain, the two end rotors can be identically oriented in a specific direction while keeping the middle rotor in its ground state, and for an equilateral triangle, two rotors can be identically oriented in a specific direction while the third rotor is oriented in the opposite direction. These multirotor unique objective cases exploit the shape of the field in coordination with dipole-dipole coupling between the rotors. Comparisons to numerically exact calculations, utilizing the TDH-determined fields, are given for all optimal control studies involving systems of three rotors.

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

Rational Design of High-Performing Electrodes in Energy Storage Devices

Rational design of interfaces with proper physico-chemical properties is necessary to optimize the performance of electrochemical devices, which requires fundamental understanding of the interfaces. In this project, we leveraged quantum mechanical and molecular dynamics simulations as well as machine learning (ML) technique to correlate the relationships between structure and properties including ion transport and electronic structures of cathode host materials in lithium-sulfur (Li-S) and carbon anode in sodium (Na) batteries for improved electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2021

Progress Towards Accelerating the Unified Model on Hybrid Multi-Core Systems

The cloud microphysics scheme, CASIM, and the radiation scheme, SOCRATES, are two computationally intensive parts within the Met Office's Unified Model (UM). This study enables CASIM and SOCRATES to use accelerated multi-core systems for optimal computational performance of the UM. Using profiling to guide our efforts, we refactored the code for optimal threading and kernel arrangement and implemented OpenACC directives manually or through the CLAW source-to-source translator. Initial porting results achieved 10.02x and 9.25x speedup in CASIM and SOCRATES respectively on 1 GPU compared with 1 CPU core. A granular performance analysis of the strategy and bottlenecks are discussed. These improvements will enable UM to run on heterogeneous computers and a path forward for further improvements is provided.

Zhang, Wei↗
DOE OSTI2017

Molecular weight and uniformity define the mechanical performance of lignin-based carbon fiber

Lignin-based carbon fiber represents a renewable and low-cost alternative to petroleum-based carbon fiber. However, the poor mechanical performance of current lignin carbon fiber hinders its application. We hypothesized that the lower optimal mechanical performance is caused by the inherent heterogeneity of lignin. It is still unknown how the molecular weights (MWs) and lignin uniformity will impact the performance of lignin carbon fiber. We thereby addressed this hypothesis by fractionating lignin into fractions with different MWs and polydispersity indices (PDIs). An enzyme–mediator-based method and a dialysis method were developed to derive lignin fractions with increased MW and decreased PDI. Lignin fractions were electro-spun into fibers after blending with polyacrylonitrile (PAN) at 1 : 1 (w/w) ratio. The fractionation in general improved the spinnability of lignin to allow us to obtain finer lignin-based carbon fibers. The elastic modulus of lignin carbon fibers, as measured by nanoindentation, was increased as the lignin MW increased and as PDI decreased. The scatter plot and linear regression revealed very good correlation between the elastic modulus and PDI, as well as certain correlation between the elastic modulus and MW. XRD and Raman spectroscopy revealed that the crystallite size and the content of the pre-graphitic turbostratic carbon increased with higher lignin MW and lower PDI, revealing the mechanism of the improvement in carbon fiber mechanical performance. Finally, this study elucidated the impacts of lignin MW and uniformity on the mechanical properties of carbon fiber, and could thus guide the development of lignin processing technologies for quality lignin-based carbon fiber.

09 BIOMASS FUELS↗
DOE OSTI2019

Compressed Optimization of Device Architectures for Semiconductor Quantum Devices

Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum-mechanical objects with unprecedented accuracy. In semiconductor quantum-dot qubits, this manipulation requires controlling the dot orbital energies, the tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, the positions of which are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the "compressed optimization of device architectures" (CODA), in order both to efficiently identify sparse sets of voltage changes that control quantum systems and to introduce a metric that can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Collecting data in the home laboratory: evolution of X-ray sources, detectors and working practices

Recent developments in X-ray crystallographic hardware related to structural biology research are presented and discussed. While the majority of macromolecular X-ray data are currently collected using highly efficient beamlines at an ever-increasing number of synchrotrons, there is still a need for high-performance reliable systems for in-house experiments. In addition to crystal screening and optimization of data-collection parameters before a synchrotron trip, the home system allows the collection of data as soon as the crystals are produced to obtain the solution of novel structures, especially by the molecular-replacement method, and is invaluable in achieving the quick turnover that is often required for ligand-binding studies in the pharmaceutical industry. There has been a continuous evolution of X-ray sources, detectors and software developed for in-house use in recent years and a diverse range of tools for structural biology laboratories are available. An overview of the main directions of these developments and examples of specific solutions available to the macromolecular crystallography community are presented in this paper, showing that data collection ‘at home’ is still an attractive proposition complementing the use of synchrotron beamlines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗