Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “setup”

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.

At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Visualization of Multi-Fidelity Approximations of Stochastic Economic Dispatch

As renewable energy generation deployment increases, the operation of electrical grids becomes more complex. Economic dispatch is part of a grid operator's regular decision process where the amount of energy to generate is determined based on the number of available generators and the actual level of energy demand. Renewable generators are inherently stochastic due to the chaotic nature of weather patterns, and thus, real-time decisions of economic dispatch become increasingly complex. Modeling efforts to assist in these decisions in the highest fidelity typically take hours to days to solve on leadership-class computers; too long for the 5-minute operational time-frame demanded of operators. Alternatively, multi-fidelity approximations can be used to predict generation levels quickly and with sufficient accuracy to be used for real-time operations. We have developed a visualization tool to demonstrate the utility of multi-fidelity approximations by displaying contextual results of economic dispatch approximations, comparisons across fidelity levels of generation levels and possible failures to meet demand, and meta-data on the modeling setup.

interactive visualization↗
DOE OSTI2026

Scalability Analysis of Quantum Models for Stress and Emotion Detection

Stress and emotion detection from high-dimensional physiological signals is a challenging task, particularly when aiming for accurate classification across diverse behavioral states. Quantum machine learning (QML) is promising for modeling such high-dimensional data, but scalability is limited by qubit resources and the exponential cost of classical statevector simulation. This work studies the scalability of quantum support vector machines (QSVMs) for binary stress detection and three-class emotion recognition (Negative/Neutral/Positive) under varying qubit counts and angle-encoding strategies. We also present a comparison study with one-feature-per-qubit (1:1) and two-features-per-qubit (2:1) mappings. Experiments are executed on HPC infrastructure using NVIDIA CUDA-Q to evaluate performance, variance, and class-dependent separability at higher-qubit setups. Results show that larger Hilbert spaces can improve peak accuracy but may increase instability. At the same time, dense 2:1 encoding yields more consistent stress detection performance. For emotion recognition, scaling improves discrimination for classes like Negative and Positive more than Neutral. We find that effective QML scaling is task-dependent and benefits more from encoding design than simply increasing qubit count.

Onim, Md. Saif Hassan [University of Tennessee, Kn↗
DOE OSTI2026

FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving

Production LLM serving must simultaneously deliver high throughput, low latency, and sufficient context capacity under non-stationary traffic and mixed request requirements. Data parallelism (DP) maximizes throughput by running independent replicas, while tensor parallelism (TP) reduces per-request latency and pools memory for long-context inference. However, existing serving stacks typically commit to a static parallelism configuration at deployment; adapting to bursts, priorities, or long-context requests is often disruptive and slow. We present Flying Serving, a vLLM-based system that enables online DP-TP switching without restarting engine workers. Flying Serving makes reconfiguration practical by virtualizing the state that would otherwise force data movement: (i) a zero-copy Model Weights Manager that exposes TP shard views on demand, (ii) a KV Cache Adaptor that preserves request KV state across DP/TP layouts, (iii) an eagerly initialized Communicator Pool to amortize collective setup, and (iv) a deadlock-free scheduler that coordinates safe transitions under execution skew. Across three popular LLMs and realistic serving scenarios, Flying Serving improves performance by up to 4.79 × under high load and 3.47 × under low load while supporting latency- and memory-driven requests.

Gao, Shouwei [ORNL]↗
DOE OSTI2020

Operando Acoustic Monitoring of SEI Formation and Long-Term Cycling in NMC/SiGr Composite Pouch Cells

Stable long-term cycling and solid-electrolyte-interphase (SEI) formation are key challenges in the design of Si/graphite composites as Li-ion battery (LIB) anode materials. Typically, these long-term cycling properties are examined in flooded half-cell settings making use of a Li-metal counter electrode and a Si/graphite working electrode. This form factor has the advantage of offering an unlimited supply of Li-ions and electrolyte, thus isolating performance degradation to the passivation of the working electrode. However, half-cell studies are ineffective in revealing performance and degradation mechanisms of the Si/graphite composite in a more commercially realistic full cell setting. This paper outlines an operando acoustic technique that can offer insights on SEI formation and capacity degradation of Si/graphite composites in a full cell setting. Through a combination of electrochemical and chemical analyses, we show that increasing passivation of the silicon particles in the Si/graphite composite anode is correlated with an increase in the acoustic time-of-flight shift. We further show that temporary loss of the acoustic signal during the first cycle is associated with significant gassing of the cell. The operando acoustic technique outlined here is low-cost, simple to setup and has the potential for localized resolution, indicating usefulness in commercial-scale Si/graphite cell quality control and diagnosis.

42 ENGINEERING↗
DOE OSTI2020

Impact Modeling and Testing of Pouch and Prismatic Cells

Understanding battery response under impact is critical to improve the safety of electrified vehicles. Nevertheless, predicting the impact behaviors of batteries is not straightforward since a battery cell usually contains hundreds of thin layers with dramatically different material properties and multiple physical processes occur simultaneously during cell deformation. Here we utilized both empirical tests and numerical models to capture the failure process of pouch and prismatic cells in various impact scenarios. In each test, a cell was hit once by an indenter dropped from a certain height. During which the cell penetration, loading force, voltage and temperature were monitored to characterize the cell’s response. Meanwhile, numerical models were developed to capture the coupled mechanical, electrical, electrochemical and thermal responses of batteries. In these models, the cell bulk was treated as a homogeneous part to achieve computational efficiency required by large-scale simulations, and it was represented by the geologic cap model that allows both shear and compaction deformation. Simulation results showed agreement with experimental data in essential features of cell behaviors during impact. Details of the test setup, model development and cell failure behaviors are presented in this paper. Additionally, capabilities, limitations and future improvement of the battery safety modeling are discussed.

25 ENERGY STORAGE↗
DOE OSTI2020

Mechanical Modeling and Testing of Pouch Cells under Various Loading Conditions

Understanding the mechanical behaviors of batteries is critical to improve battery safety since mechanical failure may directly lead to short-circuits. Nevertheless, mechanical modeling of batteries is challenging since a cell usually contains multiple thin layers with drastically different material properties, and they exhibit different responses under different loading conditions. In this work, we developed a mechanical model for a large-format pouch cell, where the cell is represented by thick shell elements that are not only computationally efficient but also account for different thickness and material properties of individual components. Moreover, the mechanical properties of active materials in electrodes are described by a continuous surface cap model that can capture both compaction and shear deformation modes and can include strain rate effect and damage. Furthermore, to evaluate the model capabilities, we conducted abuse tests under various loading conditions (quasi-static compression, shear and impact). It is shown that the model prediction of load-displacement relationship and failure condition agree with experimental results, which demonstrates that the developed model can capture the mechanical behaviors of a cell in different abuse events. Details of element formulation, material parameters evaluation and test setup are presented. Capabilities, limitations and future directions of model development are also discussed.

25 ENERGY STORAGE↗
DOE OSTI2022

Modeling Isotope Separation in Electrochemical Lithium Deposition

Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

The Poor Academic’s DC-Offset for Reversing Polarity in Electrochemical Cells: Application to Redox Flow Cells

We provide a simple and inexpensive manual DC-offset method for extending the accepted voltage range of a battery cycler to negative voltages, without interfering with the actual operation of the electrochemical cell under the test or exceeding the voltage specs of the battery cycler instrument. We describe the working principles of the method and validate the proposed setup by operating short-term and long-term redox flow battery cycling using compositionally symmetric cell, with open-circuit voltage of zero, and full cell configurations. The method can be used to extend the capability of battery cycler instrumentation to operate any electrochemical cell that requires the polarity to be reversed during operation. Applications include cycling of other symmetric cells (e.g., Li-ion cells), implementation of polarity reversal steps for rejuvenation of electroactive species or rebalancing electrochemical cells, and alternating polarity for electrochemical synthesis.

25 ENERGY STORAGE↗
DOE OSTI2023

Long-Term Stability of Ferri-/Ferrocyanide as an Electroactive Component for Redox Flow Battery Applications: On the Origin of Apparent Capacity Fade

We assess the suitability of potassium ferri-/ferrocyanide as an electroactive species for long-term utilization in aqueous organic redox flow batteries. A series of electrochemical and chemical characterization experiments was performed to distinguish between structural decomposition and apparent capacity fade of ferri-/ferrocyanide solutions used in the capacity-limiting side of a flow battery. Our results indicate that, in contrast with previous reports, no structural decomposition of ferri-/ferrocyanide occurs at tested pH values as high as 14 in the dark or in diffuse indoor light. Instead, an apparent capacity fade takes place due to a chemical reduction of ferricyanide to ferrocyanide, via chemical oxygen evolution reaction. We find that this parasitic process can be further exacerbated by carbon electrodes, with apparent capacity fade rates at pH 14 increasing with an increased ratio of carbon electrode surface area to ferricyanide in solution. Based on these results, we report a set of operating conditions that enables the long-duration cycling of alkaline ferri-/ferrocyanide electrolytes and demonstrate how apparent capacity fade rates can be engineered by the initial system setup. If protected from direct exposure to light, the structural stability of ferri-/ferrocyanide anions allows for their practical deployment as electroactive species in long duration energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2023

High-Throughput Electrochemical Characterization of Aqueous Organic Redox Flow Battery Active Material

The development of redox-active organics for flow batteries providing long discharge duration energy storage requires an accurate understanding of molecular lifetimes. Herein we report the development of a high-throughput setup for the cycling of redox flow batteries. Using common negolyte redox-active aqueous organics, we benchmark capacity fade rates and compare variations in measured cycling behavior of nominally identical volumetrically unbalanced compositionally symmetric cells. We propose figures of merit for consideration when cycling sets of identical cells, and compare three common electrochemical cycling protocols typically used in battery cycling: constant current, constant current followed by constant voltage, and constant voltage. Redox-active organics exhibiting either high or low capacity fade rates are employed in the cell cycling protocol comparison, with results analyzed from over 50 flow cells.

Electrochemistry↗
DOE OSTI2024

Leveraging Temperature-Dependent (Electro)Chemical Kinetics for High-Throughput Flow Battery Characterization

The library of redox-active organics that are potential candidates for electrochemical energy storage in flow batteries is exceedingly vast, necessitating high-throughput characterization of molecular lifetimes. Demonstrated extremely stable chemistries require accurate yet rapid cell cycling tests, a demand often frustrated by time-denominated capacity fade mechanisms. We have developed a high-throughput setup for elevated temperature cycling of redox flow batteries, providing a new dimension in characterization parameter space to explore. We utilize it to evaluate capacity fade rates of aqueous redox-active organic molecules, as functions of temperature. We demonstrate Arrhenius-like behavior in the temporal capacity fade rates of multiple flow battery electrolytes, permitting extrapolation to lower operating temperatures. Collectively, these results highlight the importance of accelerated decomposition protocols to expedite the screening process of candidate molecules for long lifetime flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Electroanalytical Exploration of Li Loss at the Solid Electrolyte-Anode Interface in Anode-Free Batteries with Polymer Electrolytes

Li loss during cycling at the solid electrolyte|anode interface strongly determines the cycle life of anode-free solid-state batteries (SSBs). Here, this loss is probed electroanalytically for polymer electrolyte (PE)-based SSBs in anode-free coin cells with practical pressures. A wide range of parameters expected to impact the measured average coulombic efficiency (CE) were explored to estimate the expected range of performance. These factors include PE type, cycling profiles, current collector type, and the presence of a thin Li seed layer. Further, low CE values in the ~50%–85% range are observed for all electrolytes and test conditions. Other than the electrolyte type, a strong dependence of the CE on the electrochemical cycling profile and the type of metallic current collector is observed. Compared to the anode-free setup, the presence of a thin (5 μ m) Li seed layer did not improve the average CE for two out of three PEs, suggesting its presence to be a weak contributor in minimizing the Li loss. This work provides baseline data on the Li losses in low-pressure anode-free configuration cells with PEs.

25 ENERGY STORAGE↗
DOE OSTI2024

In Situ Liquid Electron Microscope Cells Strongly Attenuate Electrochemical Behavior

In situ electrochemical Scanning Transmission Electron Microscopy (ec-S/TEM) probes the dynamics of electrochemical processes in real time and at high spatial resolution. This method utilizes microfabricated electrochemical cells, with enclosed dimensions of 800 μm wide, 800 μm long, and 1–2 μm tall, with electron-transparent silicon nitride windows. Working, counter, and reference electrodes in the configuration studied are deposited Pt with a planar surface area of about 1 μm 2 and a height of 50 nm. The cell confines the electrolyte within a 1 μm tall channel, and the microfabricated electrodes have a non-standard geometry, are coplanar, and are not front-facing. As such, standard assumptions of electrochemical experiments do not apply. COMSOL modeling was used to compare and contrast differences in electrochemical behavior between conventional experimental setups and the in situ ec-S/TEM cells. Cell height strongly affected voltammogram measurements: peak magnitudes and shifts correlate directly to cell height. Reactant concentration above the electrode quickly decreases during deposition, leading to a planar diffusion-dominated regime. The concentration gradient prioritizes particle growth along the thin edges of the electrode and not on the planar part of the electrode. Experiments done in the ec-S/TEM ex situ of a TEM verify the model’s accuracy.

Wittman, Reed M. [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Modeling Losses in a Three Electrode System Towards Fast Charge Control

In this work we demonstrate the applicability of a versatile separator-reference mounted electrode in a three-electrode setup to accurately capture the primary current pathway in the battery cell during operation, calibrate a porous electrode model to the individual anode and cathode potential signals, and assign the various resistances to electrochemical phenomena in the battery cell. This calibrated electrochemical model is validated using continuous rate discharges associated with highway driving scenarios in an electric vehicle, and in turn utilized to predict the local anode potential and proximity to lithium plating onset. Finally, we demonstrate the strategy associated with utilization of the model to estimate constant anode potential charging during fast charge scenarios at various rates and starting conditions as a future look to fast charge calibration development and controls.

Garrick, Taylor R. (ORCID:0000000322518129)↗
DOE OSTI2026

Conditional Latent Diffusion for High-Resolution Prediction of Electrochemical Surface Morphology

A conditionally guided generative latent diffusion process that is trained on a set of experimental processing parameters and their associated resulting electron microscope images of the electrodeposition process is able to interpolate between processing parameters in a physically consistent way. Electrodeposition of rhenium with pulse and pulse-reverse waveforms is used as a model system, and the process is adaptable to other electrodeposition, electropolishing, or corrosion processes. The method is able to extrapolate, predicting estimates of material morphologies for experimental setups unseen in the training data. The results are demonstrated with experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Optimized Tandem Catalyst Patterning for CO 2 Reduction Flow Reactors

Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts’ reaction pathways to maximize overall system performance. This study presents a proof of concept showing the integration of continuum transport modeling with design optimization in a simplified two-dimensional flow reactor setup for electrochemical CO 2 reduction. Ag catalysts provide the CO 2 ⟶ CO reaction capability, and Cu catalysts provide the CO ⟶ high-value products reaction capability. Given a set of input parameters, the optimization algorithm uses adjoint methods to modify the Ag/Cu surface patterning in order to maximize the current density toward high-value products, such as ethylene. The optimized designs yield significant performance enhancement especially at more negative applied voltages (i.e., stronger surface reactions) and for larger numbers of patterning sections. For an applied voltage of −1.7 V vs. SHE, the 12-section optimized design increases the current density toward ethylene by up to 65% compared to the unoptimized 2-section design. For the optimized cases, observed differences in the production and consumption of CO (the key intermediate species) and minimized zones of low CO reactant surface concentration on Cu sections explain the improved reactor performance.

CO2 reduction↗
DOE OSTI2022

Multi-Scale Modeling of Hydrogen Transport in a Porous Fuel Cell Anode

Proton-exchange-membrane fuel cells (PEMFC) are a clean energy conversion alternative to traditional fossil-fuel combustion; however, transport resistances in the electrode pose a lower-limit to catalyst loading and commercialization of PEMFCs. PEMFCs consist of simultaneous hydrogen (H 2 ) oxidation and oxygen (O 2 ) reduction at the anode and cathode, respectively. Here, while oxygen transport resistances in PEMFCs have been widely studied both experimentally and analytically, hydrogen transport resistances are less understood. Herein, we present a physics-based model that encompasses multi-scale transport within the anode side of the PEMFC. The O 2 in the cathode here is omitted and replaced with H 2 to deconvolute O 2 transport resistance contributions, similar to that of a hydrogen pump. Replication of the hydrogen pump setup allows for comparison of the model against experimental analysis of H 2 gas-transport resistance in H 2 limiting-current experiments, which can also inform gas transport (including oxygen) in general. Herein, we present a multi-scale analytical model of the porous anode catalyst layers and individual catalyst agglomerates that enables determination of the effects of electrode morphology such as agglomerate size, catalyst loading, etc. on H 2 transport resistance through the porous electrode to complement and better understand H 2 limiting current experiments and deconvolute local H 2 transport resistances.

Zhang, Rosa↗
DOE OSTI2021

Characterizing possible failure modes in physics-informed neural networks (characterizing-pinns-failure-modes) v0.1.0

This software provides an implementation of the physics-informed neural network setup for different differential equations. It provides a way to solve differential equations using machine learning, via a physical constraint term in the loss function. Physics-informed neural networks are a popular approach, but here, the failures of such an approach are characterized and better solutions and training procedures are provided.

Krishnapriyan, Aditi↗