Rethinking the Design of Ionic Conductors Using Meyer?Neldel?Conductivity Plot
Explore the source record for details and available documents.
Gao, Yirong↗
SEARCH · Engineering Papers
Results for “fast optimization”
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.
Implementation of a Mesh refinement algorithm into the quasi-static PIC code QuickPIC
Plasma-based acceleration (PBA) has emerged as a promising candidate for the accelerator technology used to build a future linear collider and/or an advanced light source. In PBA, a trailing or witness particle beam is accelerated in the plasma wave wakefield (WF) created by a laser or particle beam driver. The WF is often nonlinear and involves the crossing of plasma particle trajectories in real space and thus particle-in-cell methods are used. The distance over which the drive beam evolves is several orders of magnitude larger than the wake wavelength. This large disparity in length scales is amenable to the quasi-static approach. Three-dimensional (3D), quasi-static (QS), particle-in-cell (PIC) codes, e.g., QuickPIC, have been shown to provide high fidelity simulation capability with 2-4 orders of magnitude speedup over 3D fully explicit PIC codes. In PBA, the witness beam needs to be matched to the focusing forces of the WF to reduce the emittance growth. In some linear collider designs, the matched spot size of the witness beam can be 2 to 3 orders of magnitude smaller than the spot size (and wavelength) of the wakefield. Such an additional disparity in length scales is ideal for mesh refinement where the WF within the witness beam is described on a finer mesh than the rest of the WF. A mesh refinement scheme is described that has been implemented into the 3D QS PIC code, QuickPIC. Very fine (high) resolution is used in a small spatial region that includes the witness beam and progressively coarser resolutions in the rest of the simulation domain. A fast multigrid Poisson solver has been implemented for the field solve on the refined meshes and a Fast Fourier Transform (FFT) based Poisson solver is used for the coarse mesh. The code has been parallelized with both MPI and OpenMP, and the parallel scalability has also been improved by using pipelining. A preliminary adaptive mesh refinement technique is described to optimize the computational time for simulations with an evolving witness beam size. Several test problems are used to verify that the mesh refinement algorithm provides accurate results. Additionally, the results are benchmarked against highly resolved simulations exhibiting near-azimuthal symmetry, performed using QPAD—a novel hybrid QS PIC code that uses a PIC description in the coordinates (r, ct – z) and a gridless description in the azimuthal angle, Φ.
Linear collider↗
Formal methods approach to the charging facility location problem for battery electric vehicles
Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Safe Electrolytes for Batteries
The demand for reliable and safe lithium-ion batteries (LIBs) for electric vehicles (EVs) and energy storage systems (ESS) necessitates the exploration of nonflammable phosphorus-based electrolytes as alternatives to the traditional flammable carbonate-based ones. However, integrating phosphorus-based electrolyte poses challenges, including capacity fading and compatibility issues with graphite material. Here, a high-throughput (HTP) electrochemical characterization method, similar to PH test paper, is introduced to fast screen compatible phosphorus-based electrolyte for use with graphite. Among 1,740 combinations of phosphorus-based electrolytes and graphite materials, 101 promising combinations are identified for further evaluation. These identified phosphorus-based electrolytes and graphite materials are evaluated and optimized in Li/Graphite half-cells and Graphite/LiFePO 4 (LFP) full-cells using commercial-level electrodes. The desolvation energy of a complex with one Li+ and four solvent molecules of phosphate or carbonate is calculated by density functional theory (DFT). Key parameters such as viscosity, ionic conductivity, and flammability of the electrolytes are thoroughly tested and optimized. The modified phosphate-dominant electrolyte (2 M LiFSI TEP/DME/EC (6/2/2, volume ratio) + 5 wt.% VEC + 5 wt.% FEC) demonstrates excellent thermal stability with lithiated graphite and showcases superior cycling performance in the Graphite/LFP full cell, surpassing prior research findings in phosphate-dominant electrolytes. By the rapid HTP screening and identification of compatible electrolyte-graphite combinations, this approach contributes to expediting the development of safer LIBs for EVs and ESS.
25 ENERGY STORAGE↗
A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles
Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times.
33 ADVANCED PROPULSION SYSTEMS↗
A high-performance FFT algorithm for vector supercomputers
Many traditional algorithms for computing the fast Fourier transform (FFT) on conventional computers are unacceptable for advanced vector and parallel computers because they involve nonunit, power-of-two memory strides. A practical technique for computing the FFT that avoids all such strides and appears to be near-optimal for a variety of current vector and parallel computers is presented. Performance results of a program based on this technique are given. Notable among these results is that a FORTRAN implementation of this algorithm on the CRAY-2 runs up to 77-percent faster than Cray's assembly-coded library routine.
Bailey, David H.↗
Chance-Constrained Guidance With Non-Convex Constraints
Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of failure) is below a user-specified bound known as the risk bound. An example problem is to drive a car to a destination as fast as possible while limiting the probability of an accident to 10(exp -7). This framework allows users to trade conservatism against performance by choosing the risk bound. The more risk the user accepts, the better performance they can expect.
FROM↗
An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6
This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).
Machine learning↗
Investigation of Benchmark $k$ eff Sensitivity and Uncertainty for 239 Pu fission in Specific Energy Ranges
Nuclear data at intermediate energies (from 1 to 100s of keV) are evaluated based on scarce differential data and theory unable to capture physics’ expected structure. There is also a lack of integral data. This is a known deficiency and is challenging to address. Calculated effective multiplication factor, k eff , values for intermediate energy experiments are ~25× further from experiment than for fast energies and are often well outside the experimental uncertainties. The goal of the PARADIGM (PARallel Approach of Differential and InteGral Measurements) project is to significantly re duce the uncertainties of intermediate energy nuclear data for 239 Pu. To this end, PARADIGM simultaneously optimizes experiments at both the Los Alamos Neutron Science Center (LANSCE) and National Criticality Experiments Research Center (NCERC). The combined set of data will inform new intermediate-energy nuclear data. By execution of differential and integral experiments, establishment of new theory, and undertaking nuclear data evaluation in parallel, the timeline to deliver improved nuclear data to users will be reduced significantly that is to three years. For the PARADIGM project, it was decided to optimize an integral experiment for two neutron energy ranges, within the full intermediate energy range. The low energy range goes from 1 to 30 keV, while the higher energy range goes from 30 to 600 keV. This work focuses on nuclear data sensitivities and uncertainties for 239 Pu fission for existing experiments in the International Criticality Safety Benchmark Evaluation Project (ICSBEP). When designing new experiments, it is important to understand what benchmarks currently exist. For a more traditional experiment design (in which a specific application model(s) exists), comparisons would be made between the application model(s) and existing benchmarks. For PARADIGM, there is no specific application model, but instead the specific nuclear data reaction and energy ranges of interest can be explored for existing benchmarks.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Analysis and Validation of PMT s Waveforms in ICARUS LArTPC Using Monte Carlo Simulations
ICARUS (Imaging Cosmic and Rare Underground Signals) serves as the Far Detector in the Short Baseline Neutrino (SBN) program at Fermilab, playing a central role in investigating the potential existence of sterile neutrinos in the eV squared mass range. The detector consists of two large Liquid Argon Time Projection Chambers (LArTPCs) with a total capacity of 760 tons of liquid Argon. A key component of the system is its array of 360 Photo-Multiplier Tubes (PMTs), which detect the scintillation light produced by charged particles in liquid Argon; the fast scintillation signal enables accurate event timing, triggering, and reconstruction. Together with the TPC and CRT systems, the PMTs ensure precise interaction time measurements, which are crucial for distinguishing neutrino interactions from cosmic-ray backgrounds. ICARUS uses Hamamatsu R5912-MOD PMTs, optimized for cryogenic temperatures, with high quantum efficiency, excellent timing resolution, low dark current (around 10 nA at 1500 V), and broad spectral sensitivity (300–650 nm). These characteristics are crucial for the efficient detection of scintillation light. Analyzing the waveforms of PMT signals allows for a detailed comparison between experimental data and Monte Carlo simulations. This analysis is fundamental for improving the accuracy of neutrino event reconstruction, enhancing detector calibration, and optimizing the detector's performance for current and future operations.
Brio, V. [Catania U.] (ORCID:0009000088807391)↗
Quantum Dynamics at Scale: Ultrafast Control of Emergent Functional Materials
Confluence of extreme-scale quantum dynamics simulations (i.e. quantum@scale) and cutting-edge x-ray free-electron laser experiments are revolutionizing materials science. An archetypal example is the exciting concept of using picosecond light pulses to control emergent material properties on demand in atomically-thin layered materials. This paper describes efforts to scale our quantum molecular dynamics engine toward the United States' first exaflop/s computer, under an Aurora Early Science Program project named "Metascalable layered material genome". Key algorithmic and computing techniques incorporated are: (1) globally-scalable and locally-fast solvers within a linear-scaling divide-conquer-recombine algorithmic framework; (2) algebraic `BLASification' of computational kernels; and (3) data alignment and loop restructuring, along with register and cache blocking, for enhanced vectorization and efficient memory access. The resulting weak-scaling parallel efficiency was 0.93 on 131,072 Intel Xeon Phi cores for a 56.6 million atom (or 169 million valence-electron) system, whereas the various code transformations achieved 5-fold speedup. The optimized simulation engine allowed us for the first time to establish a significant effect of substrate on the dynamics of layered material upon electronic excitation.
Algebraic BLASification↗
Fast Integer Ambiguity Resolution for GPS Attitude Determination
In this paper, a new algorithm for GPS (Global Positioning System) integer ambiguity resolution is shown. The algorithm first incorporates an instantaneous (static) integer search to significantly reduce the search space using a geometric inequality. Then a batch-type loss function is used to check the remaining integers in order to determine the optimal integer. This batch function represents the GPS sightline vectors in the body frame as the sum of two vectors, one depending on the phase measurements and the other on the unknown integers. The new algorithm has several advantages: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can resolve the integers even when coplanar baselines exist. The performance of the new algorithm is tested on a dynamic hardware simulator.
Lightsey, E. Glenn↗
Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery
Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.
42 ENGINEERING↗
Characterization of sub-picosecond laser-produced fast electrons by modeling angularly resolved bremsstrahlung measurements with 3D hybrid particle-in-cell code
Hard x-rays produced by intense laser-produced fast electrons interacting with solids are a vital source for producing radiographs of high-density objects and implosion cores for inertial confinement fusion. Accurate calculation of hard x-ray sources requires a three-dimensional (3D) simulation geometry that fully models the electron transport dynamics, including electron recirculation and the generation of absolute photon yields. To date, 3D simulations of laser-produced bremsstrahlung photons over tens of picoseconds and code benchmarking have not been performed definitively. In this study, we characterize sub-picosecond laser-produced fast electrons by modeling angularly resolved bremsstrahlung measurements for refluxing and non-refluxing targets using the 3D hybrid particle-in-cell (PIC), Large Scale Plasma code. Bremsstrahlung radiation and escaped electron data were obtained by focusing a 50-TW Leopard laser (15 J, 0.35 ps, 2 × 10 19 W/cm 2 ) on a 100-μm-thick Cu foil and a Cu with a large plastic backing (Cu–CH target). Data for both the Cu and Cu–CH targets were reproduced for simulations with a given set of electron parameters. Comparison of the simulations revealed that the hard x-ray emission from the Cu target was significantly longer in duration than that from the Cu–CH target. Here, the benchmarked hybrid PIC code could prove to be a powerful tool in the design and optimization of time- and angular-dependent bremsstrahlung sources for flash x-ray and gamma-ray radiography.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Synchrotron‐source micro‐x‐ray computed tomography for examining butterfly eyes
Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro-x-ray computed tomography (syn-μXCT) combined with machine learning algorithms for high-throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm 3 at 600 nm 3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species-independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.
59 BASIC BIOLOGICAL SCIENCES↗
Operando S/TEM Reactions of Pt/TiO 2 Catalysts for Catalytic Fast Pyrolysis
Conversion of lignocellulosic biomass into the transportation fuel is an attractive concept. Using ex situ Catalytic Fast Pyrolysis (CFP) improves to upgrade bio-oils via catalytic deoxygenation of the biomass pyrolysis vapors. Zeolites are often used in this technique as the catalyst; however, in order to reduce minimum fuel selling price and improve carbon yields, ongoing research emphasizes catalyst optimization. By using bifunctional metal-acid catalysts and utilizing hydrogen, it is possible to improve carbon yields by minimizing the carbon-containing light gasses (since oxygen is removed aswater) and by reducing coke formation. Current research and development activities focuses on Pt/TiO 2 catalysts as the most promising catalyst candidates for the hydrodeoxygenation process. Here, our aim is to determine the structure-function relationships of the Pt/TiO 2 catalyst and the role of Pt dispersions within the catalyst on performance, using operando scanning transmission electron microscopy (S/TEM).
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effect of energetic ions on edge-localized modes in tokamak plasmas
The most efficient and promising operational regime for the International Thermonuclear Experimental Reactor tokamak is the high-confinement mode. In this regime, however, periodic relaxations of the plasma edge can occur. These edge-localized modes pose a threat to the integrity of the fusion device. Here we reveal the strong impact of energetic ions on the spatio-temporal structure of edge-localized modes in tokamaks using nonlinear hybrid kinetic–magnetohydrodynamic simulations. A resonant interaction between the fast ions at the plasma edge and the electromagnetic perturbations from the edge-localized mode leads to an energy and momentum exchange. Energetic ions modify, for example, the amplitude, frequency spectrum and crash timing of edge-localized modes. The simulations reproduce some observations that feature abrupt and large edge-localized mode crashes. The results indicate that, in the International Thermonuclear Experimental Reactor, a strong interaction between the fusion-born alpha particles and ions from neutral beam injection, a main heating and fast particle source, is expected with predicted edge-localized mode perturbations. This work advances the understanding of the physics underlying edge-localized mode crashes in the presence of energetic particles and highlights the importance of including energetic ion kinetic effects in the optimization of edge-localized mode control techniques and regimes that are free of such modes.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Rubisco Function, Evolution, and Engineering
Carbon fixation is the process by which CO 2 is converted from a gas into biomass. The Calvin–Benson–Bassham cycle (CBB) is the dominant carbon-consuming pathway on Earth, driving >99.5% of the ~120 billion tons of carbon that are converted to sugar by plants, algae, and cyanobacteria. The carboxylase enzyme in the CBB, ribulose-1,5-bisphosphate carboxylase/oxygenase (rubisco), fixes one CO 2 molecule per turn of the cycle into bioavailable sugars. Despite being critical to the assimilation of carbon, rubisco's kinetic rate is not very fast, limiting flux through the pathway. This bottleneck presents a paradox: Why has rubisco not evolved to be a better catalyst? Many hypothesize that the catalytic mechanism of rubisco is subject to one or more trade-offs and that rubisco variants have been optimized for their native physiological environment. Here, we review the evolution and biochemistry of rubisco through the lens of structure and mechanism in order to understand what trade-offs limit its improvement. We also review the many attempts to improve rubisco itself and thereby promote plant growth.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗