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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Microwave-Assisted Plastic Upcycling: Dynamic Data Reconciliation, Parameter Estimation, and Kinetic Modeling

Microwave (MW)-assisted catalytic pyrolysis offers a promising pathway for efficient plastic upcycling. This work develops an integrated modeling framework combining dynamic data reconciliation, a temperature-dependent rate model, and a yield model to represent the time-varying production rate of components in MW-assisted LDPE pyrolysis conducted in a batch reactor. An Arrhenius-type rate model with a temperature-dependent reaction order is developed. A biexponential correlation is proposed for the yield of gaseous products that enables to capture the evolving product formation behavior during conversion. In the yield correlation, one term is used to represent the initial increase in yield, reflecting the rapid formation of intermediate or primary products at the early stages of the reaction when a larger fraction of the reactant remains available. As conversion progresses, the influence of this term gradually diminishes. The other term accounts for the subsequent decrease in the predicted yield, representing secondary reactions such as further cracking or coke formation that reduce the concentration of certain products at higher conversion. The model is found to accurately represent reconciled experimental flow rate profiles from an in-house MW-assisted catalytic batch reactor for major products, including ethylene, ethane, 1-butene, and benzene, across 250−350 °C. Ethylene remains the dominant product but decreases from about 41.95% at 250 °C to 30.14% at 350 °C, while heavier products increase significantly, with 1-butene rising to nearly 8.37% and benzene reaching 2.17% at intermediate temperatures. The model shows that the ethylene production rate can be maximized at around 270 °C. The models developed in this work can be utilized for process optimization, reactor design and scale-up of microwave-assisted plastic conversion technologies, and economic analysis.

Damahe, Harish [West Virginia Univ., Morgantown, W↗
DOE OSTI2023

Record high room temperature resistance switching in ferroelectric-gated Mott transistors unlocked by interfacial charge engineering

Abstract The superior size and power scaling potential of ferroelectric-gated Mott transistors makes them promising building blocks for developing energy-efficient memory and logic applications in the post-Moore’s Law era. The close to metallic carrier density in the Mott channel, however, imposes the bottleneck for achieving substantial field effect modulation via a solid-state gate. Previous studies have focused on optimizing the thickness, charge mobility, and carrier density of single-layer correlated channels, which have only led to moderate resistance switching at room temperature. Here, we report a record high nonvolatile resistance switching ratio of 38,440% at 300 K in a prototype Mott transistor consisting of a ferroelectric PbZr 0.2 Ti 0.8 O 3 gate and an R NiO 3 ( R : rare earth)/La 0.67 Sr 0.33 MnO 3 composite channel. The ultrathin La 0.67 Sr 0.33 MnO 3 buffer layer not only tailors the carrier density profile in R NiO 3 through interfacial charge transfer, as corroborated by first-principles calculations, but also provides an extended screening layer that reduces the depolarization effect in the ferroelectric gate. Our study points to an effective material strategy for the functional design of complex oxide heterointerfaces that harnesses the competing roles of charge in field effect screening and ferroelectric depolarization effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Machine learning surrogate of physics-based building-stock simulator for end-use load forecasting

Building energy models are used to simulate heat and mass transfer and estimate end-use load in buildings. With the proliferation of solar photovoltaics on residential and commercial buildings, increasingly, buildings are expected to provide grid services, for which accurate and computationally efficient building energy simulations and end-use load prediction are imperative. Existing building energy simulation tools, however, have significant computational overhead that make them less practical in real-time deployment for optimization, design, uncertainty quantification and control in building energy management systems. Here this article presents a data-driven machine learning model based on light gradient boosting method (LightGBM) as a surrogate for a physics-based simulator for residential buildings to predict end-use load. The machine learning based surrogate model accounts for time-series related variables, seasonality and trend component of end-use load, and history of end-use load. The accuracy of the surrogate model is assessed on the prediction of the load profiles of 100 different houses in Cook County, Illinois, USA. The LightGBM surrogate model is shown to reduce the root-mean-squared error by 53% relative to a reference decision tree (DT) based model reported previously in the literature. Moreover, the model predicts the load spikes and high-ramp rate events throughout the year which are often the Achilles heel of other models in the literature. The machine learning based surrogate model is demonstrated to be computationally efficient, with a ten-fold reduction in the computational time compared to a physics-based building energy simulation, and suitable for uncertainty analysis and real-time control of building characteristics in response to uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

KALYPSO: Linear array detector for high-repetition rate and real-time beam diagnostics

Synchrotrons and modern FEL light sources operate with bunch repetition rates in the MHz range. The profile of the electron beam inside the accelerator can be characterized with indirect experimental techniques where linear array detectors are employed to measure the emitted synchrotron radiation or the spectrum of a near-IR laser. To improve the performance of modern beam diagnostics we have developed KALYPSO, a detector system operating with a continuous frame rate of up to 2.7 MHz. To facilitate the integration in different experiments, a modular architecture has been adopted. Different semiconductor micro-strip sensors can be connected to front-end ASICs to optimize the quantum efficiency at different photon energies, ranging from visible light up to near-IR. The front-end electronics are integrated within an heterogeneous DAQ consisting of FPGAs and GPUs, which allows scientists to implement real-time data processing algorithms. The current version of the detector is in operation at the KARA synchrotron light source and at the European XFEL. Finally, in this contribution we present the detector architecture, the performance results and the on-going technical developments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Numerical minimization of neoclassical poloidal viscosity for supersonic equilibria in tokamak geometry

Extensive experimental evidence has shown that the presence of poloidal flow in tokamaks can dramatically improve transport properties. However, theory indicates that poloidal flows are damped by poloidal viscosity, thus necessitating external drivers, such as neutral beam injection or radio frequency heating. In this work, ideal magnetohydrodynamic equilibria are calculated via the FORTRAN code FLOW [Guazzotto et al., Phys. Plasmas 11, 604 (2004)] and a postprocessor is used to estimate the neoclassical poloidal viscosity. The equilibrium inputs, which correspond to intuitive physical quantities, are then numerically optimized to reduce a viscosity figure of merit. We present supersonic equilibria in tokamak geometry with minimized neoclassical poloidal viscosities for various velocity free function inputs, plasma aspect ratios, and collisionality regimes. Benchmarks are made against an analytic theory as well as a classical expression of poloidal viscosity. Numerical confirmation of the analytic theory is obtained in the high aspect ratio and high collisionality limit. Good agreement is also seen near the plasma core and edge, with discrepancies arising in the intermediate region. Outside of these limits, rotation input function profiles are found that provide ∼order of magnitude improvements over the analytic theory, with additional progress being made toward predictions for tokamak-relevant equilibria.

Physics↗
DOE OSTI2022

Predicting variations of the least principal stress with depth: Application to unconventional oil and gas reservoirs using a log-based viscoelastic stress relaxation model

Knowledge of layer-to-layer variations of the least principal stress, S hmin , with depth is essential for optimization of multi-stage hydraulic fracturing in unconventional reservoirs. Utilizing a geomechanical model based on viscoelastic stress relaxation in relatively clay rich rocks, we present a new method for predicting continuous S hmin variations with depth. The method utilizes geophysical log data and S hmin measurements from routine diagnostic fracture injection tests (DFITs) at several depths for calibration. We consider a case study in the Wolfcamp formation in the Midland Basin, where both geophysical logs and values of S hmin from DFITs are available. We compute a continuous stress profile as a function of the well logs that fits all of the DFITs well. We utilized several machine learning technologies, such as bootstrap aggregation (or bagging), to improve the generalization of the model and demonstrate that the excellent fit between predicted and observed stress values is not the result of over-fitting the calibration points. The model is then validated by accurately predicting hold-out stress measurements from four wells within the study area and, without recalibration, accurately predicting stress as a function of depth in an offset pad about 6 miles away.

58 GEOSCIENCES↗
DOE OSTI2019

High-resolution wall temperature measurements with distributed fiber optic sensors

Conventional approaches of surface temperature measurement are often unreliable, and other methods may not be practical in closed, high-temperature spaces. In this study, surface temperature measurements of the cooling panel of a natural circulation facility were performed with fiber optic distributed temperature sensors (DTS). High resolution surface temperature profiles of the cooling panel were acquired under two steady experimental conditions, and compared with measurements performed with nearby thermocouples. The total measurement error of the DTS results presented has been estimated to be ±4.4 °C. The findings reflected herein show that these DTS can reasonably measure surface temperature when installed with the methods developed in this study. Through the analysis of the DTS data collected, the interesting behavior of the cooling panel was revealed, providing new insights on the system's behavior that may be beneficial to the design and optimization of such heat transfer devices. These sensors can also provide the measurement density necessary for validation efforts with highly-resolved prediction methods such as finite element analysis (FEA) or computational fluid dynamics (CFD).

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Ultrasonic Nondestructive Diagnosis of Cylindrical Batteries Under Various Charging Rates

Lithium-ion batteries have been used increasingly as electrochemical energy storage systems for electronic devices and vehicles. It is important to accurately estimate the state of charge (SoC) of a battery management system to control the battery operation to optimize performance, lifetime, and safety. The current work experimentally leverages ultrasonic diagnostic technology to investigate the SoC of lithium-ion batteries during the charge/discharge processes. A cylindrical-type nickel-cobalt-aluminum (NCA)–based 2500mAh 20A (INR18650-25R) battery was used for ultrasonic measurements with various charge/discharge rates of C/10.4, C/5.2, and C/1.3 at constant currents. The ultrasonic signals were analyzed for extracting wave velocity and wave attenuation. For all the testing rates, wave velocity increased in the charge process and decreased in the discharge process. Further, velocity profiles corresponding to lower rates of C/10.4 and C/5.2 exhibited primary peaks at the maximum SoCs, whereas the absolute wave velocity of C/1.3 rate showed primary peaks that occurred slightly after the SoC peak, indicating a delayed maximum Young's modulus. The wave attenuation computed for the C/10.4 rate had local maxima in the charge and discharge processes and depicted negative correlations with SoC, ranging from 0% to 18%, and positive correlations with SoC from 18% to 85%. On the other hand, the wave attenuation curves of the C/1.3 rate showed no local peaks and had negative correlations with SoC, ranging from 0% to 28%, and positive correlations with SoC ranging from 28% to 53%.

25 ENERGY STORAGE↗
DOE OSTI2024

Off-Design Load Analysis of sCO2 Bottoming Cycle for a Natural Gas Combined Cycle Power Plant with Carbon Capture

This work starts with the optimal design from Pidaparti et. al (2024) to analyze the off-design performance of the power plant from 100% down to 50% load. The main operational findings and plant-efficiency for off-load conditions while maintaining the target CO2 capture rate are presented. The goal of the work is to determine if there is a relative advantage or disadvantage for the sCO2 bottoming cycle compared to the steam bottoming cycle in terms of reduced load efficiency performance for the NGCC with carbon capture. Results show nearly identical efficiency profiles for the two cases from 100% to 50% load.

Chinen, Anderson Soares↗
DOE OSTI2021

Real-Time Data Acquisition and Processing System for MHz Repetition Rate Image Sensors

An electro-optic detector is one of the diagnostic setups used in particle accelerators. It employs an electro-optic crystal to encode the longitudinal beam charge profile in the spectrum of a light pulse. The charge distribution is then reconstructed using data captured by a fast spectrometer. The measurement repetition rate should match or exceed the machine bunching frequency, which is often in the range of several MHz. A high-speed optical line detector (HOLD) is a linear camera designed for easy integration with scientific experiments. The use of modern FPGA circuits helps in the efficient collection and processing of data. The solution is based on Xilinx 7-Series FPGA circuits and implements a custom latency-optimized architecture utilizing the AXI4 family of interfaces. HOLD is one of the fastest line cameras in the world. Thanks to its hardware architecture and a powerful KALYPSO sensor from KIT, it outperforms the fastest comparable commercial devices.

MicroTCA↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2018

Impact of Heat Dissipation Profiles on Power Electronics Packaging Design

This work focuses on understanding the thermal impacts of using discrete power devices and limitations of applying conventional thermal design methods. Empirically, a thermal system is designed based on selecting a heat sink with the required thermal resistance from the manufacturer datasheet. This method, as an approximate estimation, has been proven effective as a rough design of Si-based power module. However, wide bandgap (WBG) bare dies bring additional thermal design concerns that have been overlooked. The benefits of WBG devices, such as smaller chip sizes and higher power ratings, on the other hand, lead to thermal concentration issues. Detailed analyses and impacts of the thermal concentration are presented in this paper. Finally, a more accurate model involving Finite Element Analysis (FEA) and Genetic Algorithm optimization is also proposed for a more accurate thermal design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Heat transfer model for moving packed-bed particle-to-sCO 2 heat exchangers integrated with metal foams

Particle-to-supercritical carbon dioxide (sCO 2 ) heat exchangers (HXs) play a vital role in coupling heat transfer fluid (HTF) from high-temperature thermal receivers to power cycle working fluids (WF). Heat transfer enhancement is essential for adopting particle-based moving packed-bed heat exchangers (MPBHXs) in next-generation thermal energy storage (TES) systems, as MPBHXs usually exhibit low particle bed-to-wall heat transfer coefficients. High-porosity metal foams have shown their effectiveness in heat transfer enhancement. Here, this work presents a continuum heat transfer model to demonstrate the heat transfer enhancement in MPBHXs when the particle bed channel is filled with high porosity metal foams compared to open channel MPBHXs. The presence of metal foams increases the effective thermal conductivity in the particle channel and enhances the interstitial heat transfer coefficient between the moving particle bed and the stationary metal foams. The present model considers coupled two-dimensional (2D) heat transfer in the particle channel with metal foams and 1D heat transfer in the sCO 2 channel and the dividing wall. The temperature profiles for the particle bed, metal foam, dividing wall, and sCO 2 stream, as well as the local heat flux profiles between those, are studied in detail for various foam porosities, from which the particle bed-to-wall heat transfer coefficient, overall heat transfer coefficient, and total heat transfer rate for the MPBHX are determined. The effects of major MPBHX design and operating parameters on the particle bed-to-wall heat transfer coefficient and overall heat exchange capacity are thoroughly examined; thus, the MPBHX performance improvement with metal foams is quantified for each case. The present heat transfer model can provide valuable insights into the metal-foam MPBHX design and optimization, scale-up, and operating parameters selection.

42 ENGINEERING↗
DOE OSTI2023

Systematically derived thermodynamic properties for alkane oxidation

Key combustion properties, such as ignition delay time, show strong sensitivity to the thermochemistry of the main species in the standard radical oxidation pathway at low temperatures (600-1000K). Significant uncertainties persist in current estimates of thermodynamic properties, particularly for the larger species of relevance to common practical fuels. In this article, we use advanced computational schemes to evaluate thermodynamic properties for the fuel, fuel radical, peroxy, hydroperoxy-alkyl radical, and hydroperoxide species for a set of 17 fuels containing up to 9 carbon atoms, and with various degrees of branching in the alkane backbone. The procedure, termed STAR-1D, combines conformer sampling to find the minimum geometry, B2PLYP-D3/cc-pVTZ harmonic frequency evaluations, and omega B97X-D/cc-pVTZ one-dimensional torsional mapping. It includes two physically-based scaling routines: a frequency-dependent scaling to B2PLYP-D3/cc-pVTZ anharmonic frequencies and a scaling of one-dimensional omega B97X-D/ccpVTZ torsional profiles to reproduce the product of the B2PLYP-D3/cc-pVTZ frequencies in the harmonic limit. Substantive comparisons with existing experimental databases, together with careful examinations of key theoretical assumptions, are used to explore the accuracy of the predictions. These computationally intensive explorations of 195 species were facilitated by automated thermochemistry software. Further, high accuracy 0 K heats of formation from a separate study are used with the STAR-1D computations to generate NASA polynomial representations. In addition to their intrinsic value, the present results also provide a reliable database for the optimization of group additivity or machine learning schemes for scaling to larger combustion systems. Towards this end a complementary extensive conformational analysis is carried out for the medium sized species and the thermodynamic properties of the lowest energy hydrogen-bonded and non-hydrogen bonded conformers are contrasted for larger hydroperoxy-alkyl radical species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Empowering multicomponent cathode materials for sodium ion batteries by exploring three-dimensional compositional heterogeneities

Affordable sodium ion batteries hold great promise for revolutionizing stationary energy storage technologies. Sodium layered cathode materials are usually multicomponent transition metal (TM) oxides and each TM plays a unique role in the operating cathode chemistry, e.g., redox activity, structural stabilization. Engineering the three-dimensional (3D) distribution of TM cations in individual cathode particles can take advantage of a depth-dependent charging mechanism and enable a path towards tuning local TM–O chemical environments and building resilience against cathode–electrolyte interfacial reactions that are responsible for capacity fading, voltage decay and safety hazards. In this study, we create 3D compositional heterogeneity in a ternary and biphasic (O3–P3) sodium layered cathode material (Na 0.9 Cu 0.2 Fe 0.28 Mn 0.52 O 2 ). The cells containing this material deliver stable voltage profiles, and discharge capacities of 125 mA h g –1 at C/10 with almost no capacity fading after 100 cycles and 75 mA h g –1 at 1C with negligible capacity fading after 200 cycles. The direct performance comparison shows that this material outperforms other materials with similar global compositions but different mesoscale chemical distributions. Synchrotron X-ray spectroscopy/imaging and density functional theory studies reveal depth-dependent chemical environments due to changes to factors such as charge compensation and strength of orbital hybridization. Finally, 3D spectroscopic tomography illuminates the path towards optimizing multicomponent sodium layered cathode materials, to prevent the migration of TMs upon prolonged cycling. Furthermore, the study reports an inaugural effort of multifaceted and counterintuitive investigation of sodium layered cathode materials and strongly implies that there is plenty of room at the bottom by tuning nano/meso scale chemical distributions for stable cathode chemistry.

25 ENERGY STORAGE↗
DOE OSTI2018

A new elliptical-beam method based on time-domain thermoreflectance (TDTR) to measure the in-plane anisotropic thermal conductivity and its comparison with the beam-offset method

Materials lacking in-plane symmetry are ubiquitous in a wide range of applications such as electronics, thermoelectrics, and high-temperature superconductors, in all of which the thermal properties of the materials play a critical part. Yet, very few experimental techniques can be used to measure in-plane anisotropic thermal conductivity. A beam-offset method based on time-domain thermoreflectance (TDTR) was previously proposed to measure in-plane anisotropic thermal conductivity. However, a detailed analysis of the beam-offset method is still lacking. Our analysis shows that uncertainties can be large if the laser spot size or the modulation frequency is not properly chosen. In this report we propose an differing approach based on TDTR to measure in-plane anisotropic thermal conductivity using a highly elliptical pump (heating) beam. The highly elliptical pump beam induces a quasi-one-dimensional temperature profile on the sample surface that has a fast decay along the short axis of the pump beam. The detected TDTR signal is exclusively sensitive to the in-plane thermal conductivity along the short axis of the elliptical beam. By conducting TDTR measurements as a function of delay time with the rotation of the elliptical pump beam to different orientations, the in-plane thermal conductivity tensor of the sample can be determined. In this work, we first conduct detailed signal sensitivity analyses for both techniques and provide guidelines in determining the optimal experimental conditions. We then compare the two techniques under their optimal experimental conditions by measuring the in-plane thermal conductivity tensor of a ZnO [11-20] sample. The accuracy and limitations of both methods are discussed.

47 OTHER INSTRUMENTATION↗