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At least 145 records · Page 8

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DOE OSTI2024

Advanced multimaterial shape optimization methods as applied to advanced manufacturing of wind turbine generators

Abstract Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline.

17 WIND ENERGY↗

DOE OSTI2024

Lithium Plating Characteristics in High Areal Capacity Li-Ion Battery Electrodes

Li-ion battery degradation and safety events are often attributed to undesirable metallic lithium plating. Since their release, Li-ion battery electrodes have been made progressively thicker to provide a higher energy density. However, the propensity for plating in these thicker pairings is not well understood. Herein, we combine an experimental plating-prone condition with robust mesoscale modeling to examine electrode pairings with capacities ranging from 2.5 to 6 mAh/cm 2 and negative to positive (N/P) electrode areal capacity ratio from 0.9 to 1.8 without the need for extensive aging tests. Using both experimentation and a mesoscale model, we identify a shift from conventional high state-of-charge (SOC) type plating to high overpotential (OP) type plating as electrode thickness increases. Further, these two plating modes have distinct morphologies, identified by optical microscopy and electrochemical signatures. We demonstrate that under operating conditions where these plating modes converge, a high propensity of plating exists, revealing the importance of predicting and avoiding this overlap for a given electrode pairing. Further, we identify that thicker electrodes, beyond a capacity of 3 mAh/cm 2 or thickness >75 μm, are prone to high OP, limiting negative electrode (NE) utilization and preventing cross-sectional oversizing the NE from mitigating plating. Here, it simply contributes to added mass and volume. The experimental thermal gradient and mesoscale model either combined or independently provide techniques capable of probing performance and safety implications of mild changes to electrode design features.

25 ENERGY STORAGE↗

NASA NTRS1974

Transient analysis of a thermal storage unit involving a phase change material

The transient response of a single cell of a typical phase change material type thermal capacitor has been modeled using numerical conductive heat transfer techniques. The cell consists of a base plate, an insulated top, and two vertical walls (fins) forming a two-dimensional cavity filled with a phase change material. Both explicit and implicit numerical formulations are outlined. A mixed explicit-implicit scheme which treats the fin implicity while treating the phase change material explicitly is discussed. A band algorithmic scheme is used to reduce computer storage requirements for the implicit approach while retaining a relatively fine grid. All formulations are presented in dimensionless form thereby enabling application to geometrically similar problems. Typical parametric results are graphically presented for the case of melting with constant heat input to the base of the cell.

Griggs, E. I.↗

NASA NTRS1985

Crystal Growth Research in Space

The objectives of this work are to develop growth techniques and theory leading to improved bulk growth of semiconductor single crystals. Ground based experiments will be complemented by experiments carried out in the low-g environment provided by the space shuttle. Analytical studies and laboratory investigations are being conducted to better define the causes of crystalline defects and inhomogeneities. The compound semiconductor lead-tin-telluride is being used as the modeling material. Theoretical techniques are being developed to predict the thermal and solutal fields which are present during bulk growth from a melt. Techniques for measuring the thermophysical properties of semiconductors at high temperatures have been developed. During the past year electrochemical etching techniques have been developed for delineation of inhomogeneous regions in crystals. Thermal diffusivity measurements have been completed for the solid and liquid phases of PbTe and PbSnTe. Preliminary results have been obtained on the effects on crystal morphology of gravity, interface shape and interaction between the melt and the container.

Crouch, R. K.↗

NASA NTRS1986

Thermal sensing of cryogenic wind tunnel model surfaces Evaluation of silicon diodes

Different sensors and installation techniques for surface temperature measurement of cryogenic wind tunnel models were investigated. Silicon diodes were selected for further consideration because of their good inherent accuracy. Their average absolute temperature deviation in comparison tests with standard platinum resistance thermometers was found to be 0.2 K in the range from 125 to 273 K. Subsurface temperature measurement was selected as the installation technique in order to minimize aerodynamic interference. Temperature distortion caused by an embedded silicon diode was studied numerically.

Daryabeigi, K.↗

NASA NTRS1986

Thermal sensing of cryogenic wind tunnel model surfaces - Evaluation of silicon diodes

Daryabeigi, Kamran↗

NASA NTRS2004

TIGER: Development of Thermal Gradient Compensation Algorithms and Techniques

In a wind tunnel facility, the direct measurement of forces and moments induced on the model are performed by a force measurement balance. The measurement balance is a precision-machined device that has strain gages at strategic locations to measure the strain (i.e., deformations) due to applied forces and moments. The strain gages convert the strain (and hence the applied force) to an electrical voltage that is measured by external instruments. To address the problem of thermal gradients on the force measurement balance NASA-LaRC has initiated a research program called TIGER - Thermally-Induced Gradients Effects Research. The ultimate goals of the TIGER program are to: (a) understand the physics of the thermally-induced strain and its subsequent impact on load measurements and (b) develop a robust thermal gradient compensation technique. This paper will discuss the impact of thermal gradients on force measurement balances, specific aspects of the TIGER program (the design of a special-purpose balance, data acquisition and data analysis challenges), and give an overall summary.

Hereford, James↗

DOE OSTI2025

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Capsule network-based semantic segmentation model for thermal anomaly identification on building envelopes

Thermography technology is widely used to inspect thermal anomalies in building façade systems. Computer vision-based techniques provide opportunities to autonomously detect such heat anomalies to significantly improve the efficiency of decision-making for building envelope retrofitting and maintenance. Here, in this work, we propose a novel Capsule Network-based deep learning model – CapsLab – that detects and identifies thermal anomalies by semantic segmentation. CapsLab is built based on our proposed prediction-tuning capsule (PT-Capsule) layer. Different from a traditional capsule layer, which consists of part-whole transformation and capsule-routing process, the proposed layer is composed of a prediction and tuning process, which helps decreasing the number of model parameters significantly. While the applicability of traditional Capsule Networks (CapsNets) has been limited to simpler tasks and smaller datasets due to their scalability issue, we can leverage the lightweight of the proposed PT-Capsule layer, and apply it to the semantic segmentation task. In this work, we also employ our previously presented performance metric, referred to as the Anomaly Identification Metric (AIM) (Kakillioglua et al. 2021), to evaluate the segmentation outputs. Traditional performance metrics do not accurately reflect the true performance of the segmentation models in thermal anomaly identification due to the high subjectivity in the annotation process and higher overlap ratio sensitivity of the standard metrics. AIM, on the other hand, is robust to these drawbacks. Experimental results show, both qualitatively and quantitatively, that our proposed segmentation method can effectively segment the thermal anomalies. Specifically, our model provides 9.38% and 13.53% improvements over the baseline model – DeepLabV3+ – based on traditional mIoU score and the AIM score, respectively, while requiring less model parameters and less computation at the same time. In addition, the scores that the AIM metric generates better align with the scores provided by building performance experts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1976

Thermal analyses of the International Ultraviolet Explorer (IUE) scientific instrument using the NASTRAN thermal analyzer (NTA): A general purpose summary

The NTA Level 15.5.2/3, was used to provide non-linear steady-state (NLSS) and non-linear transient (NLTR) thermal predictions for the International Ultraviolet Explorer (IUE) Scientific Instrument (SI). NASTRAN structural models were used as the basis for the thermal models, which were produced by a straight forward conversion procedure. The accuracy of this technique was sub-sequently demonstrated by a comparison of NTA predicts with the results of a thermal vacuum test of the IUE Engineering Test Unit (ETU). Completion of these tasks was aided by the use of NTA subroutines.

Jackson, C. E., Jr.↗

NASA NTRS1976

Effective thermal property improves phase change paint data

The phase-change coating technique presents itself as a valuable tool in determining the heat transfer rate over the surface of small complex wind tunnel models. A numerical technique is described which shows that an effective thermophysical property - the square root of the product of thermal conductivity, density, and specific heat - may significantly improve the accuracy of the phase-change coating technique with allowance for model inhomogeneity and temperature dependency in a transient environment. Results of the measured steady-state variation of the effective thermophysical property with temperature and the effect of surface heating rate on the effective thermophysical property are plotted for a representative homogeneous model material and for an extreme nonhomogeneous model material. The use of an effective thermophysical property to reduce phase-change paint data is recommended. The analysis also confirms that the apparatus described by Corwin and Kramer (1975) can be used to measure directly this effective thermophysical property for use in wind tunnel model heat-transfer measurements.

Drummond, J. P.↗

NASA NTRS1979

Thermal analysis of Bridgman-Stockbarger growth

A thermal analysis of a cylindrical HgCdTe sample in a Bridgman-Stockbarger crystal growth configuration was conducted with emphasis on the thermal profile, interface shape and position, and the thermal gradients at the liquid-solid interface. Alloys of HgTe and CdTe with compositions approximating 20 percent CdTe, 80 percent HgTe were used. This composition results in a bandgap suited for the detection of 10.6 micron CO2 radiation. The sensitivity of the sample thermal characteristics to important growth parameters, such as thermal diffusivities, thermal conductivities, furnace temperature profile, ampoule dimensions, and growth velocity was assessed. Numerical techniques and associated computational models necessary to analyze the heat transfer process within the sample and the Bridgman-Stockbarger boundary conditions were developed. This thermal analysis mode was programmed in FORTRAN V, and is currently operational on the MSFC Univac 1100 system.

Knopf, F. W.↗

NASA NTRS2018

Total Temperature Measurements Using a Rearward Facing Probe in Supercooled Liquid Droplet and Ice Crystal Clouds

Engine Icing Performance loss: rollback, surge, flameout, and even internal engine damagePartial melting and refreeze of ice inside engine core (Mason et al., 2006). Ingestion of ice crystals and aggregates, mixed-phase droplets, or supercooled liquid dropletsNeed to better understand the conditions and properties that lead to engine icing.Simulation and analysis (physical and computational, and modeling)Test facilities (PSL, NRC, ...). Thermal and computational models and analysisProbesMultiple probes (aerothermal probes and ice cloud characterization probes and techniques). Total temperatureTraditional total temperature probes (vented forward facing)Heated total temperature probes (Goodyear). Rearward facing (developmental). Total temperature relevance. Thermal interaction between the icing cloud and air flow impinging particles contribute to kinetic heating effect (Gent et al., 2000). Measurement considerations Temperature sensor accuracy. Incomplete recovery of total temperature. Thermal surfaces (sources and sinks). Flow effects (viscous losses). Debris contamination, including icing and ice ingestion.

Agui, Juan H.↗

NASA NTRSDate not supplied

Finite Element Thermal Model for Ultrasonic Welding of Thermoplastic Composites

Ultrasonic welding, UW, is a fast and energy-efficient technique for joining thermoplastic composites. It involves the use of high-frequency mechanical vibrations and a static welding force to melt and join adherends. Ultrasonic welding is an enabling technology to reduce the cost and complexity of in-space construction because lightweight thermoplastic composite components can be packaged compactly for launch and then efficiently assembled using supervised autonomous robotic technologies on site. However, the temperatures in space present challenges to UW, and it is critical that the efficacy of process parameters selected for manufacturing in space is understood prior to launch. To this end, a three-dimensional finite element model is presented in this technical presentation. The model incorporates equations for effects of viscoelastic heating and heat transfer on the welding process. The proposed model is applied to predict the temperature distribution in single lap shear, SLS, samples composed of AS4/PEEK (TC1200) composite that were welded using a terrestrial machine as part of a comprehensive weldability study. Thermocouple and infrared spot sensor data from the SLS samples provide empirical temperature measurements for calibration and validation of the UW thermal model. Calibration and validation of the model is an important step given the significant uncertainties in material properties such as the loss modulus and necessary assumptions in the physics implementations which allow the model to converge in an acceptable amount of time. The validated thermal model can be used to simulate the process for the space environment. Future validation sample testing is planned in a vacuum chamber. The result will be a model capable of guiding process parameter selection to ensure acceptable weld bonds when manufacturing in space.

Josh Fody↗

NASA NTRS1999

Thermal Conductivity and Elastic Modulus Evolution of Thermal Barrier Coatings under High Heat Flux Conditions

Laser high heat flux test approaches have been established to obtain critical properties of ceramic thermal barrier coatings (TBCs) under near-realistic temperature and thermal gradients that may he encountered in advanced engine systems. Thermal conductivity change kinetics of a thin ceramic coating were continuously monitored in real time at various test temperatures. A significant thermal conductivity increase was observed during the laser simulated engine heat flux tests. For a 0.25 mm thick ZrO2-8%Y2O3 coating system, the overall thermal conductivity increased from the initial value of 1.0 W/m-K to 1. 15 W/m-K, 1. 19 W/m-K and 1.5 W/m-K after 30 hour testing at surface temperatures of 990C, 1100C, and 1320C. respectively. Hardness and modulus gradients across a 1.5 mm thick TBC system were also determined as a function of laser testing time using the laser sintering/creep and micro-indentation techniques. The coating Knoop hardness values increased from the initial hardness value of 4 GPa to 5 GPa near the ceramic/bond coat interface, and to 7.5 GPa at the ceramic coating surface after 120 hour testing. The ceramic surface modulus increased from an initial value of about 70 GPa to a final value of 125 GPa. The increase in thermal conductivity and the evolution of significant hardness and modulus gradients in the TBC systems are attributed to sintering-induced micro-porosity gradients under the laser-imposed high thermal gradient conditions. The test techniques provide a viable means for obtaining coating data for use in design, development, stress modeling, and life prediction for various thermal barrier coating applications.

Zhu, Dongming↗

DOE OSTI2021

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗

DOE OSTI2022

CO 2 zonal injection rate allocation and plume extent evaluation through wellbore temperature analysis

Temperature analysis during a pause in injection operations, known as warmback analysis, has been used in the petroleum industry for evaluating the injection conformance and estimating the location of the flooded front in applications, such as waterflooding oil reservoirs. Here in this work, methods are introduced to extend the application of temperature warmback analysis to estimate the zonal CO 2 injection rate and zonal CO 2 plume extent during geologic CO 2 storage in a saline aquifer. First, novel analytical solutions are developed to model transient temperature in the aquifer during the injection and subsequent shut-in periods considering two-phase flow (gaseous CO 2 and aqueous brine) conditions in the aquifer. The solution involves a discretization of the aquifer into regions; the energy and mass conservation equations for the regions are solved simultaneously considering appropriate boundary conditions at the interfaces. Two solutions techniques are presented: multi-region and three-region solutions. Inverse models are developed accordingly to evaluate the injection profile and estimate the extent of the plume front in the reservoir during the injection period. The multi-region solution results in an inversion approach that requires regression analysis. However, the three-region formulation results in a simple graphical technique for inverse modeling. The analytical solutions are validated against a thermally coupled reservoir simulation tool using different synthetic cases for CO 2 injection in deep saline aquifers. The results of the developed solutions provide a good match with numerical results during forward and inverse modeling.

54 ENVIRONMENTAL SCIENCES↗