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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Stress localization investigation of additively manufactured GRCop-42 thin-wall structure

A full-field crystal plasticity (CP) framework is presented for the GRCop-42 alloy to study microscopic mechanical behavior and local stress heterogeneities. The microstructures of additively manufactured (AM) materials are often unique relative to conventionally processed materials, and the local thermal histories drive these differences during the build process. These thermal histories depend on the process parameters (laser power, scan speed, and scan strategy) and the part geometry. Prior research has shown that the mechanical properties of thin-walled structures can vary significantly with wall thickness due to changes in the thermal boundary conditions during manufacturing. It is, therefore, desirable to perform CP simulations based on the phenomenological constitutive model to predict the local mechanical responses induced by microstructural heterogeneities. This work generates representative microstructures based on experimentally collected grain information (i.e., texture) for grain scale stress analysis, and the material constitutive parameters are calibrated using the experimental mechanical testing data. Here, we specifically investigated the effect of crystallographic texture and grain morphologies on the size-dependent mechanical properties of AM GRCop-42. The selection of appropriate material properties for implementing an effective free surface boundary condition and the influence of adjacent buffer layers are also discussed. Analysis of local field results reveals a strong correlation between stress localization and the initial grain orientation. However, no significant relationship between the misorientation of the individual adjacent grains and the average misorientation is observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermomechanical Modeling and Analysis of a High-Temperature Light Trapping Planar Cavity Receiver

Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.

concentrating solar power↗
DOE OSTI2022

De novo transcriptome sequencing of Capsicum frutescens . L and comprehensive analysis of salt stress alleviating mechanism by Bacillus atrophaeus WU ‐9

Abstract Salt stress, as one of the most severe environmental stresses, can cause a series of changes in plants. However, the explanation of plant salt stress alleviating mechanism of plant growth–promoting rhizobacteria (PGPR) was hindered by the limited availability of transcriptomic information for salt stress‐treated plants grown in a microorganism‐controlled environment. Our previous reports have selected Bacillus atrophaeus WU‐9 as PGPR significantly alleviating pepper ( Capsicum frutescens . L) salt stress. In this work, the RNA‐seq analysis of salt stress‐treated and untreated plants, grown with and without WU‐9 in a microorganism‐controlled environment, was used to reveal the plant salt stress alleviating mechanisms of WU‐9. Twelve sequencing libraries, prepared by treating with WU‐9 and salt (150 mM NaCl for 36 h), were constructed by RNA‐Seq technique. Non‐inoculated seedlings mainly respond to salt stress through regulation of signal transduction, such as ethylene‐activated signaling pathway, signaling and cell communication, etc. And ethylene signal participated in salt stress response in pepper through regulating defense responses, fruit ripening and senescence. WU‐9 inoculation under salt stress mainly improves salt tolerance and plant growth by regulating salt stress‐responding ethylene and auxin signal transduction, utilization of proline, photosynthesis, antioxidant enzyme activities and cell enlargement. Furthermore, 86 differentially expressed genes and 20 transcription factors were identified as associated with salt stress response and tolerance. Thus, this innovative transcriptomic study identified the salt stress response and alleviation in C. frutescens . L with PGPR inoculation. This result provided novel insights into the salinity alleviation in pepper regulated by PGPR.

Wang, Wenfei↗
DOE OSTI2024

SOSAT: Geohazard Risk Assessment in Carbon Sequestration Operations

Like all operations in which fluids are injected into the subsurface, geologic carbon storage (GCS) presents inherit risks that must be assessed and mitigated to successfully deploy such technology in the field. For example, alterations to pore pressure and the stress state due to fluid injection may trigger certain geohazards, such as potential fault activation and induced seismicity or unintentional hydraulic fracturing. Here we present capabilities for assessing these potential risks using the State of Stress Analysis Tool (SOSAT): a Python library and web-based application capable of probabilistically estimating the subsurface state of stress informed by various field observations. Using posterior distributions of principal stress components, SOSAT can assess the risk of fault activation within the injection formation for either a critically oriented fault or a fault with a user-prescribed orientation. Additionally, SOSAT can estimate the probability of unintentional hydraulic fracturing of the intact reservoir rock. Here, we demonstrate these SOSAT capabilities using a hypothetical GCS site. This type of risk assessment can assist with the effective deployment of GCS technology in the field by informing safe design and management practices.

Haagenson, Ryan J.↗
DOE OSTI2020

Interlaboratory Reproducibility of Contour Method Data Analysis and Residual Stress Calculation

While the contour method for residual stress assessment has developed rapidly, no published study documents its interlaboratory reproducibility. Objective: Here we report an initial reproducibility experiment focused on contour method data analysis and residual stress calculation. The experiment uses surface topography data from a physical process simulation of elastic-plastic beam bending. The simulation provides surface topography, for input to the contour method data analysis, as well as a known residual stress field with 130 MPa peak magnitude. Additionally, to increase realism, noise and specific artifacts are added to the topography data. A group of participants received the topography data (without the known residual stress), independently analyzed the data, and submitted results as a two-dimensional residual stress field. Analysis of submissions provides a group average residual stress field and the spatial distribution of reproducibility standard deviation. The group average residual stress agrees with the known stress in magnitude and spatial trend. The reproducibility standard deviation ranges from 2 to 54 MPa over the measurement plane, with an average of 5.4 MPa. Reproducibility standard deviation is smaller in the cross-section interior (≤ 5 MPa), modest near local extrema in the stress field (5 to 10 MPa), and larger near the cross-section boundaries (10 to 30 MPa). Overall, the largest values of reproducibility standard deviation (up to 54 MPa) occur in limited areas where artifacts had been added to the topography data; while some participants identified and removed these artifacts, some did not, leading to systematic differences that elevated the standard deviation.

42 ENGINEERING↗
DOE OSTI2022

Quantitative texture analysis at the WAND 2 and HIDRA diffractometers

Data collection and analysis strategies have been developed for efficient and reliable crystallographic texture measurements at two recently upgraded neutron diffractometers: the Wide Angle Neutron Diffractometer Squared (WAND 2 ) and the High Intensity Diffractometer for Residual Stress Analysis (HIDRA) at the High Flux Isotope Reactor located at Oak Ridge National Laboratory. These methods are demonstrated using measurements on a variety of textured samples, including multi-phase steel composites and polycrystalline calcite (CaCO 3 ). Reference measurements were also made at VULCAN, the engineering diffractometer located at the Spallation Neutron Source. The texture data obtained on the different instruments are in agreement, and WAND 2 is more time efficient than HIDRA. Two analysis methods were investigated, single-peak fitting to obtain individual pole figures for inversion and Rietveld texture analysis using MAUD. Here, the impact of the differences between the various textures obtained was evaluated through the calculation of diffraction elastic constants, which is one application of the texture data collected. Both instruments were found to provide texture data that are suitable for complementing other analyses, such as residual stress mapping.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗
DOE OSTI2022

Thermal Ratcheting Analysis of TEDS Packed-bed Thermocline Energy Storage Tank - Modeling Methodology and Data Validation

This report investigates numerical modeling methods for thermal ratcheting analysis of packed-bed thermal energy storage (TES) tank and discusses the validation results via comparison with experimental data. The experimental data obtained from various design characteristics of packed-bed thermocline tanks, including the Thermal Energy Distribution System (TEDS) TES tank at Idaho National Laboratory (INL), were used to validate thermal and mechanical models developed in this study to evaluate the thermal ratcheting potential. The thermal model was shown to predict the transient thermal propagation through the packed-bed thermocline tanks generally well. However, a larger discrepancy was observed during the comparison with the data from TEDS, presumably due to the uncertainty of boundary conditions given from the experiment. Based on the comparative study between the thermal model predictions and experimental data of various packed-bed thermocline tanks, potential improvements were suggested for the future TEDS experiments for more precise validation study. For mechanical (thermally induced stress) analysis, two different modeling approaches were tested to evaluate hoop stress applied to the packed-bed TES tank wall, which is a major cause of thermal ratcheting process: (i) infinite rigidity model and (ii) Drucker-Prager (DP) model. The ‘model (i)’ is a conservative method with infinite rigidity assumption of granular filler inside a TES tank, whereas the ‘model (ii)’ is a method that takes into account more realistic processes such as thermal expansion of filler and tank wall as well as inter-particle interactions during the cyclic operation of a packed-bed TES tank. The validity of each modeling method was examined by comparing the numerical simulation with the experimental data obtained from the packed-bed TES tank for Solar One pilot plant. Then, the effects of various model parameters were discussed to evaluate the thermal ratcheting potential of the TEDS TES tank. The preliminary thermal ratcheting analysis implies that the TEDS TES tank will hold its structural integrity during the normal operation cycles.

25 ENERGY STORAGE↗
DOE OSTI2022

Topology optimization of an airfoil fin microchannel heat exchanger using artificial intelligence

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, is analyzed and optimized using a design of experiments with artificial intelligence techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin printed circuit heat exchangers (PCHEs) has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure is developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. Computational fluid dynamics is used to analyze a simplified two-channel configuration where five design parameters are varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods (a 5D polynomial and a regression neural network) are compared for generating surrogate models and the resulting response surface approximation is input to a genetic algorithm that is used to identify a set of optimal parameters. The optimal geometries are found across six channel Reynolds numbers ranging from 1000 to 5000, since inlet conditions affect flow through the heat exchanger. Additionally, a set of optimal designs that maximizes heat transfer and minimizes pressure drop is identified, and a thermal stress analysis is performed on the optimal design. Correlations for the Nusselt number and Darcy friction factor are developed that can be useful for thermal hydraulic analyses using system codes. Thermal stresses are analyzed and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2021

Finite Element Analysis (FEA) for Water-Foam Fracturing of Granite Rock

In addition to the foam data that were obtained from literature and that were collected from the current study, simulation data was also generated from finite element analysis (FEA) conducted in this study using COMSOL Multiphysics software. The FEA models were built to simulate the experiments conducted at Oak Ridge National Laboratory (ORNL) on cement and granite samples. In these FEA models, temperature was kept at ambient while the pressure profile resembled the loading conditions during the ORNL experiments, where pressure was either monotonically increased or applied cyclically. The cement material was used as a model material and was used to study Von Mises stress and tensile stress distribution for different bore hole length geometry using a parametric sweep with water as fracturing fluid using solid-fluid interaction module. For the granite material, FEA models were developed for stress analysis of cylindrical samples with water or foam fluids. The solid mechanics module in COMSOL was implemented to solve for Von Mises stress and tensile stress. The fluid-structure interaction module was implemented to solve for water-foam interaction on granite cylinder with addition of fluid-loading on structure, i.e., large deformation in solid mechanics with no impact on fluid deformation. Foam was considered as a pseudo single-phase compressible fluid for which material properties were calculated from water and gas (nitrogen) phases. The density of foam is calculated as a function of the densities of water and nitrogen, while viscosity is a function of temperature. Four types of FEA analyses were modelled: 1. Monotonic injection with water 2. Monotonic injection with foam 3. Cyclic injection with water 4. Cyclic injection with foam All the COMSOL files are converted to a zip file which is save in .mph.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

EcoBOT: an AI/ML enabled automated phenotyping capability for model plants

Introduction: Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching small model plants under axenic conditions and integrate it with AI/ML tools. Methods: The EcoBOT platform was developed, which consists of sterile containers (EcoFABs) for growing plants and imaging for monitoring plant growth and health. Brachypodium distachyon was grown on the EcoBOT, and its response to nutrient limitation and copper stress was evaluated. Results: The results showed that Brachypodium distachyon grown in the EcoBOT maintained sterility and responded to nutrient limitation and copper stress. Analysis of over 6,500 root and shoot images revealed varying sensitivity and response rates to copper. Bayesian Optimization was used to improve model accuracies relating copper concentrations to plant biomass via sequential experiments, resulting in a >30% improvement. Discussion: The findings of this study demonstrate the potential of the EcoBOT platform for researching plant responses to environmental factors. Future experiments could focus on relating other chemical stresses and microbial interactions to create generalized models of plant responses.

AI image analysis↗
DOE OSTI2021

A Novel Approach for Bounding the Stress Experienced by the Core of Utility-Scale Printed Circuit Heat Exchangers Under Thermohydraulic Loads

Printed circuit heat exchangers (PCHEs) have rapidly gained popularity since being introduced nearly three decades ago, and they are currently widely deployed in the petrochemical and aviation industry. Their compactness, thermohydraulic efficiency, inherent suitability for high temperature/pressure fluids containment, and demonstrated durability are some of the reasons the nuclear industry is seeking to adopt this technology as well. However, the relatively strict nuclear-related regulatory design code, especially when classified as critical to the safety of the reactors, is posing challenges to adopting the technology. From stress analysis point of view, one undesirable feature of PCHEs is their geometrical complexity, which is implied by their multilength-scale features. As a result, a full-scale model of a utility-scale exchanger cannot simply be solved on a computer because meshing such components results in a vast number of degrees-of-freedom. Here, this work seeks to address the challenge of stress analyses to PCHEs by presenting a method to simplify the geometry of PCHE designs. The models proposed by this work can be practically analyzed on a standard computer and provide a path for implementing ASME design rules. The analyses presented herein are divided into five separate investigations. Each is carried out to incrementally simplify the analyzed model by addressing features such as the shapes of the flow passages, the complex distribution of stress in large components, the three-dimensionality of the stress and strain, the thermal stresses caused by thermohydraulic operation observed experimentally and more.

42 ENGINEERING↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. Further, the MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10%. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11%. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

42 ENGINEERING↗
DOE OSTI2024

Development of a high-temperature Inconel 625 heat exchanger by model design and binder jetting additive manufacturing

A nickel-based Inconel 625 superalloy heat exchanger for high-temperature applications was developed via binder jetting additive manufacturing. The material properties were characterized first on printed and sintered parts. Two sintering temperatures were used to investigate the effects of the temperature on densification and microstructure. For channel geometry design, the heat transfer capabilities of the heat exchanger were optimized for the cross-section geometry of fluid flow channels in a counterflow configuration, and a stress analysis was conducted to investigate the effects of channel geometry. After headers were incorporated into the heat exchanger as a one-piece component, a prototype was printed. A complete depowdering was achieved via compressed air blowing, and sintering was performed with the developed profile. Ultimately, a one-piece heat exchanger with a nearly full density was obtained. Heat transfer tests were performed on this unit, and the results were compared with those from the simulations. In this study, systematic processes were developed for an additively manufactured Inconel-based heat exchanger for high-pressure, high-temperature heat transfer applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Micro-beam bending of FCC bicrystals: A comparison between defect dynamics simulations and experiments

To understand the role of the grain boundary (GB) in plasticity at small scale, a concurrently coupled mesoscale plasticity model was developed to simulate micro-bending of bicrystalline micron-sized beams. By coupling dislocation dynamics (DD) with a finite element model (FEM), a novel defect dynamics model provides the means to investigate intricate interactions between dislocations and GBs under various loading conditions. Our simulations of micro-bending agree well with corresponding micro-bending experiments, and they show that mechanical response of bicrystals could have not only hardening but also softening depending on the characters of the GB. In addition, changing the location of the GB in the microbeams results in different mechanical responses; GBs located at the neutral plane show softening compared to single crystals, while inclined GBs located halfway along the length of the beam show little effect. In conclusion, simulation results could provide a clear picture on detailed dislocation-GB interactions, and quantitative resolved shear stress analysis supplemented by dislocation density distribution is used to analyze the mechanical response of bicrystalline samples.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermal shock resistance of multilayer silicon carbide receiver tubes for 800°C molten salt concentrating solar power application

CSP power tower receiver systems during rapid transient weather periods can be vulnerable to thermal shock conditions from rain that which can facilitate the onset of leaks and failures that can have catastrophic consequences. Silicon carbide (SiC) materials have attractive receiver application characteristics for being light weight, having high-strength and excellent thermal shock resistance performance which make them a particularly good fit for receiver absorber materials in CSP. In this investigation, the performance characteristics of Ceramic Tubular Products (CTP) SiC ceramic matrix composite (CMC), multilayered tubes were explored with respect to thermal shock performance for solar receiver applications in next generation CSP plants. Here, thermal shock testing was performed at the Sandia National Laboratories (SNL) Solar Furnace facility using a dynamic stage and thermal shock tube test setup. The tubes tested under incident solar heat flux of 100 W/cm2 were heated with inner tube temperatures reaching approximately 800 °C, with outer temperatures exceeding or just reaching 1000 El for the multilayer and monolithic SiC tubes respectively. The tubes were then quenched with simulated rain. The tubes were then cooled and subjected to hoop stress analysis using an Instron device to assess their subsequent mechanical strength. Furthermore, the on-sun study experimental results indicate an average of 24.2% and 97% higher hoop strength for the CMC tubes than those composed of monolithic SiC and aluminum oxide (A1203) respectively.

14 SOLAR ENERGY↗
DOE OSTI2020

Controllable Solar Flux Heating for Freeze Recovery in Molten Salt Parabolic Trough Collectors

In molten-salt parabolic trough plants, the melting process is particularly important for freeze recovery of salt that is solidified in a collector loop, should such an event occur. Currently impedance heating is expected for freeze recovery of the collector loops, but this method can be expensive. Here, a lower-cost alternative is proposed to use controllable concentrated solar flux directly from the parabolic mirrors to thaw salt that is frozen in the collector. A computational fluid dynamics model was developed to explore the solidification and melting processes of molten salt in a parabolic trough receiver and to assess the viability of this concept. Results indicate that concentrated solar heating has the potential to melt frozen salt in 5.6 h, compared to that in 8.8 h for a 300 W m –1 impedance heating system. At the same time, controllable solar flux heating introduces nonuniform solar fluxes on the receiver surface, which can induce significant thermal stress on the receiver tube. A preliminary stress analysis indicates that the temperature difference across the receiver tube should be maintained below about 70 °C for heating up to 300 °C at internal pressures ≤10 bar. At these conditions, freeze recovery using solar flux heating will not significantly affect receiver lifetime. These results suggest that controllable solar flux heating could effectively supplement or replace impedance heating in the freeze recovery system. Incorporating this methodology in future parabolic trough concentrating solar power plants is an opportunity for capital and operational cost-savings.

14 SOLAR ENERGY↗