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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adaptively remeshed multiphysical modeling of resistance forge welding with experimental validation of residual stress fields and measurement processes

Welding processes used in the production of pressure vessels impart residual stresses in the manufactured component. Computational modeling is critical to predicting these residual stress fields and understanding how they interact with notches and flaws to impact pressure vessel durability. Here, in this work, we present a finite element model for a resistance forge weld and validate it using laboratory measurements. Extensive microstructural changes, near-melt temperatures, and large localized deformations along the weld interface pose significant challenges to Lagrangian finite element modeling. The proposed modeling approach overcomes these roadblocks in order to provide a high-fidelity simulation that can predict the residual stress state in the manufactured pressure vessel; a rich microstructural constitutive model accounts for material recrystallization dynamics, a frictional-to-tied contact model is coordinated with the constitutive model to represent interfacial bonding, and adaptive remeshing is employed to alleviate severe mesh distortion. An interrupted-weld approach is applied to the simulation to facilitate comparison to displacement measures. Several techniques are employed for residual stress measurement in order to validate the finite element model: neutron diffraction, the contour method, and the slitting method. Model-measurement comparisons are supplemented with detailed simulations that reflect the configurations of the residual-stress measurement processes themselves. The model results show general agreement with experimental measurements, and we observe some similarities in the features around the weld region. Factors that contribute to model-measurement differences are identified. Finally, we conclude with some discussion of the model development and residual stress measurement strategies, including how to best leverage the efforts put forth here for other weld problems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analysis of chemical stress and the propensity for cracking during the vertical Bridgman growth of BaBrCl:Eu

Computational models are employed to analyze residual chemical stresses arising from compositional variations in europium-doped BaBrCl crystals grown by the vertical Bridgman method. We find that significant chemical stress is produced by radial segregation of Eu in this system. In particular, the distribution of normal stresses is set by the radial concentration gradient, whose changing sign produces surface states in tension or compression. Additionally, crack opening from surface flaws will be promoted or suppressed by tensile or compressive surface stresses, respectively. Thus, crystal growth processing strategies that change the radial dopant concentration gradients are posited to affect the propensity for cracking. For this system, surface stresses are changed from states of tension to compression when the growth rate is increased, thus improving the chances to avoid cracking—a strategy that defies classical wisdom that dictates slower growth to improve outcomes. Similar strategies affecting segregation may prove beneficial to tailor chemical stress fields to reduce cracking in other crystal growth systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Behavioral simulations and experimental evaluations of stress induced spatial nonuniformity of dynamic bulk modulus in additive friction stir deposited AA 6061

Additive friction stir deposition (AFSD) is a rapidly developing solid-state additive manufacturing (AM) technology that enables the fabrication of customized products on a relatively large scale. The unique forge-liked process offers high quality products with refined equiaxed microstructure and exceptional mechanical performance. However, in AFSD, the spatially distributed mechanical properties within a deposited layer have not been established so far, due to the lack of a suitable large-scale mapping method. In the present work, an ultrasonic dynamic-elasticity mapping method was employed to map the distribution of physical properties in a AFSD 6061 Al. Strong spatial asymmetries in elastographies were mainly due to the residual stresses. The origin of the asymmetries was investigated through thermo-mechanical simulations of the AFSD process. It was observed that majority of the asymmetries were associated with the mechanical residual stresses instead of the symmetric thermal residual stresses during linear deposition of the AFSD process. However, the thermal residual stresses can be manipulated to become asymmetric with a 90° turn in the linear deposition path, due to the difference between the levels of cooling along the edges of the inner and outer corners. Hence, the mechanical and thermo-mechanical residual stresses can be additive or subtractive depending on the direction of the turns. Here, such numerically predicted behaviors were also experimentally observed on the AFSD fabricated samples by ultrasonic elastography. Furthermore, additional preliminary studies on multi-layer AFSD fabrications show the asymmetric mechanical stresses generated during the deposition process on different layers generate constructive or destructive interference which results to spatially variable dynamic bulk modulus depending on the deposition orientations of layers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measuring residual stress in Ti-6Al-4V with HR-EBSD, using reference patterns from annealed material

In this study, elastic strain and residual stress values in an engineering material were determined by high-resolution EBSD (HR-EBSD) using reference patterns from annealed, recrystallized material. Specifically, rolled Ti-6Al-4V sheet was analyzed using HR EBSD in both an as-annealed and a strained state, the latter established via a static two-point bend fixture. The commercial software CrossCourt4 (CC4) was used to evaluate the relative intragranular strain tensor components of the alpha grains mapped by HR-EBSD. The intragranular reference patterns identified in each grain by the software were then replaced with similarly-oriented patterns from scans of the as-annealed, recrystallized material. The CC4 analysis was then repeated to provide calibrated strain and residual stress values. Elastic strains on the order of 10–3 were detected, with corresponding residual stress values on the order of 1 GPa. Subsequent analyses using high energy synchrotron x-ray diffraction showed good correlation with the elastic strains measured by HR-EBSD using the annealed reference patterns. Additionally, the maximum macroscopic stress analytically predicted for two-point bending was in agreement with the residual stress observed. Good repeatability of the methodology and insight into the state of individual grains were also observed. The findings provide encouraging evidence that accurate intragranular and long-range residual stress measurements of engineering significance can be made with HR-EBSD using a physical reference pattern library.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Subpicosecond Optical Stress Generation in Multiferroic BiFeO 3

We report optical excitation leads to ultrafast stress generation in the prototypical multiferroic BiFeO 3 . The time scales of stress generation are set by the dynamics of the population of excited electronic states and the coupling of the electronic configuration to the structure. X-ray free-electron laser diffraction reveals high-wavevector subpicosecond-time scale stress generation following ultraviolet excitation of a BiFeO 3 thin film. Stress generation includes a fast component with a 1/e rise time with an upper limit of 300 fs and longer-rise time components extending to 1.5 ps. The contributions of the fast and delayed components vary as a function of optical fluence, with a reduced a fast-component contribution at high fluence. The results provide insight into stress-generation mechanisms linked to the population of excited electrons and point to new directions in the application of nanoscale multiferroics and related ferroic complex oxides. The fast component of the stress indicates that structural parameters and properties of ferroelectric thin film materials can be optically modulated with 3 dB bandwidths of at least 0.5 THz.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Stress-Dependent Chemo-Mechanical Performance of Amorphous Si Anodes for Li-Ion Batteries upon Lithiation

Alloying-type anodes are significantly governed by their chemo-mechanical performance during the electrochemical cycling. The reaction-induced huge volumetric change of these anodes may cause material degradation and failure under mechanical constraints. Here, we investigate the stress-dependent lithiation behavior of amorphous Si (a-Si) anodes using molecular dynamics simulations. It is indicated that a-Si anodes can sustain higher hydrostatic stress than biaxial/uniaxial ones without the occurrence of mechanical failure. Thermodynamic and electrochemical calculations demonstrate that although the lithiation procedure also affects the thermodynamic stability of a-Si anodes, it is mainly dominated by the external mean stresses. Compressive stress is confirmed to destabilize a-Si anodes and further trigger their capacity fading. Compared with our atomistic simulations, previous continuum models underestimate the open-cell potentials of a-Si anodes, due to their ignored large volumetric deformation at higher stresses and Li concentrations. Finally, this computational study provides the intensive atomic-level understanding of the stress-dependent lithiation behavior of a-Si anodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes

Abstract Seismic hazard forecasts of induced seismicity often require estimates of the maximum possible magnitude ( M max ). Empirical models suggest that maximum magnitudes, or expected number of earthquakes, are related to the volume of injected fluid. We perform a suite of 3D physics‐based earthquake simulations with rate‐ and state‐dependent friction, systematically varying the area of the pressurized region and the amplitude of the initial homogeneous or heterogeneous shear stress. Using the resulting catalog we explore the conditions that result in pressure‐controlled versus runaway ruptures that extend outside the pressurized zone. We find that proposed empirical scaling laws correctly predict M max when shear stresses are further from failure (≤90% of maximum shear stress) and for high amplitude stress fields. Runaway ruptures are observed for higher initial shear stresses and smoother stress fields. In these cases, runaway ruptures occur early after the onset of injection and rarely preceded by foreshock activity.

58 GEOSCIENCES↗
DOE OSTI2021

Residual strain-stress in manganese steel railway crossing determined by synchrotron and laboratory X-rays

The residual stress within the nose of a worn manganese steel railway crossing was investigated. The macroscopic residual stress at the running surface was determined in areas with and without visual faults by laboratory X-rays. To get information about the penetration depth of the residual stress, synchrotron X-ray diffraction was used to map the distribution of local (within grain) residual strains below the running surface. The laboratory X-ray measurements revealed significant compressive stress on the rail running surface. The synchrotron measurements documented that local strains exist through the entire depth investigated. Relations between residual stress, plastic deformation, and crack formation are analysed, leading to a discussion on potentials/limitations of the two experimental methods for investigations of residual stress in large engineering components.

differentia aperture synchrotron diffraction↗
DOE OSTI2023

$S$ Hmax orientation in the Alpine region from observations of stress-induced anisotropy of nonlinear elasticity

The orientation of $S$ Hmax is commonly estimated from in situ borehole breakouts and earthquake focal mechanisms. Borehole measurements are expensive, and therefore sparse, and earthquake measurements can only be made in regions with many well-characterized earthquakes. Here, we derive the stress-field orientation using stress-induced anisotropy in nonlinear elasticity. In this method, we measure the strain derivative of velocity as a function of azimuth. We use a natural pump-probe (NPP) approach which consists of measuring elastic wave speed using empirical Green’s functions (probe) at different points of the earth tidal strain cycle (pump). The approach is validated using a larger data set in the Northern Alpine Foreland region where the orientation of maximum horizontal compressive stress is known from borehole breakouts and drilling-induced fractures. The technique resolves NNW-SSW to N-S directed $S$ Hmax which is in good agreement with conventional methods and the recent crustal stress model. We confirm that the NPP method can be applied to dense large-scale seismic arrays. The technique is then applied to the Southern Alps to understand the contemporary stress pattern associated with the ongoing deformation due to counterclockwise rotation of the Adriatic plate with respect to the European plate. Our results explain why the two major faults in Northeastern Italy, the Giudicarie Fault and the Periadriatic Line (Pustertal–Gailtal Fault) are currently inactive, while the currently acting stress field allows faults in Slovenia to deform actively. We have demonstrated that the pump-probe method has the potential to fill in the measurement gap left by conventional approaches, both in terms of regional coverage and in depth.

58 GEOSCIENCES↗
DOE OSTI2025

Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops

Abiotic stresses such as drought, heat, cold, salinity and flooding significantly impact plant growth, development and productivity. As the planet has warmed, these abiotic stresses have increased in frequency and intensity, affecting the global food supply and making it imperative to develop stress-resilient crops. In the past 20 years, the development of omics technologies has contributed to the growth of datasets for plants grown under a wide range of abiotic environments. Integration of these rapidly growing data using machine-learning (ML) approaches can complement existing breeding efforts by providing insights into the mechanisms underlying plant responses to stressful conditions, which can be used to guide the design of resilient crops. In this review, we introduce ML approaches and provide examples of how researchers use these approaches to predict molecular activities, gene functions and genotype responses under stressful conditions. Finally, we consider the potential and challenges of using such approaches to enable the design of crops that are better suited to a changing environment. This article is part of the theme issue ‘Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the ‘Resilience Revolution’?’.

abiotic stress↗
DOE OSTI2022

On Residual Stresses and Reference Temperatures in Thermomechanical Simulations of Photovoltaic Modules Using the Finite Element Method

Thermomechanical simulation of photovoltaic (PV) modules using the finite element method (FEM) is a useful tool to evaluate module design features in terms of structural integrity, reliability, and durability. One of the main challenges in the numerical modeling of a PV module is the incorporation of residual stresses induced by the manufacturing process. Modeling assumptions and abstractions are necessary to limit the model complexity and reduce the computational time. However, oversimplifications and incorrect assumptions can lead to erroneous numerical results. Unfortunately, much simulation work still neglects process-induced stresses. This can lead to incorrect predictions of the stress-strain history and erroneous conclusions during the design process. In this work, we review current modeling practices for incorporating process-induced stresses, and contrast numerical models that consider residual stresses with those that neglect them. We find that the simulation objective and available material properties dictate which process steps need to be modeled, and explore in depth the modeling of residual stresses induced by the lamination process. We demonstrate that a simplified cooldown procedure at the beginning of the simulation can increase the model accuracy and discuss appropriate choices for starting and reference temperatures in the finite element model.

14 SOLAR ENERGY↗
DOE OSTI2020

Correlation of Advanced Accelerated Stress Testing with Polyamide-Based Photovoltaic Backsheet Field-Failures

Cracking of polyamide (PA)-based photovoltaic (PV) backsheet materials has been widely reported for field-aged modules. Failure was not detected by conventional accelerated stress tests (ASTs), which lacked the necessary combination of stress factors and/or factor sequences. PA-based AAA backsheet cracking has since been reproduced through combined and sequential stress testing. Planar- and cross-sectional-optical microscopy as well as Fourier-transform Infrared Spectroscopy (FTIR), have been used to elucidate the mechanical and chemical changes which lead to failure of the backsheet. Field-aged backsheet samples demonstrating failure in various climates (including locations in China and Italy) are also analyzed. Through the analysis, a comparison is made between the different stress testing protocols and the field-aged samples to validate relevance of the advanced stress tests. It is shown that the changes induced through combined-accelerated stress testing (C-AST) were most representative of changes induced by the field, supporting the relevance of C-AST and providing validity for the test protocol.

14 SOLAR ENERGY↗
DOE OSTI2021

De novo transcriptome in roots of switchgrass ( Panicum virgatum L. ) reveals gene expression dynamic and act network under alkaline salt stress

Background: Soil salinization is a major limiting factor for crop cultivation. Switchgrass is a perennial rhizomatous bunchgrass that is considered an ideal plant for marginal lands, including sites with saline soil. Here we investigated the physiological responses and transcriptome changes in the roots of Alamo (alkaline-tolerant genotype) and AM314/MS-155 (alkaline-sensitive genotype) under alkaline salt stress. Results: Alkaline salt stress significantly affected the membrane, osmotic adjustment and antioxidant systems in switchgrass roots, and the ASTTI values between Alamo and AM-314/MS-155 were divergent at different time points. A total of 108,319 unigenes were obtained after reassembly, including 73,636 unigenes in AM-314/MS-155 and 65,492 unigenes in Alamo. A total of 10,219 DEGs were identified, and the number of upregulated genes in Alamo was much greater than that in AM-314/MS-155 in both the early and late stages of alkaline salt stress. The DEGs in AM-314/MS-155 were mainly concentrated in the early stage, while Alamo showed greater advantages in the late stage. These DEGs were mainly enriched in plant-pathogen interactions, ubiquitin-mediated proteolysis and glycolysis/gluconeogenesis pathways. We characterized 1480 TF genes into 64 TF families, and the most abundant TF family was the C2H2 family, followed by the bZIP and bHLH families. A total of 1718 PKs were predicted, including CaMK, CDPK, MAPK and RLK. WGCNA revealed that the DEGs in the blue, brown, dark magenta and light steel blue 1 modules were associated with the physiological changes in roots of switchgrass under alkaline salt stress. The consistency between the qRT-PCR and RNA-Seq results confirmed the reliability of the RNA-seq sequencing data. A molecular regulatory network of the switchgrass response to alkaline salt stress was preliminarily constructed on the basis of transcriptional regulation and functional genes. Conclusions: Alkaline salt tolerance of switchgrass may be achieved by the regulation of ion homeostasis, transport proteins, detoxification, heat shock proteins, dehydration and sugar metabolism. These findings provide a comprehensive analysis of gene expression dynamic and act network induced by alkaline salt stress in two switchgrass genotypes and contribute to the understanding of the alkaline salt tolerance mechanism of switchgrass and the improvement of switchgrass germplasm.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2020

Predicting Plant-Soil Feedback in the Field: Meta-Analysis Reveals That Competition and Environmental Stress Differentially Influence PSF

Past research on plant-soil feedbacks (PSF), largely undertaken in highly controlled greenhouse conditions, has established that plant species differentially alter abiotic and biotic soil conditions that in turn affect growth of other conspecific and heterospecific individuals in that soil. Yet, whether feedbacks under controlled greenhouse conditions reflect feedbacks in natural environments where plants are exposed to a range of abiotic and biotic pressures is still unresolved. To address how environmental context affects PSF, we conducted a meta-analysis of previously published studies that examined plant growth responses to multiple forms of competition, stress, and disturbance across various PSF methodology. We asked the following questions: (1) Can competition, stress, and disturbance alter the direction and/or strength of PSF? (2) Do particular types of competition, stress, or disturbance affect the direction and/or strength of PSF more than others? and (3) Do methods of conducting PSF research (i.e., greenhouse vs. field experiments and whether the source of soil inoculum conditioning is from the field vs. greenhouse) affect plant growth responses to PSF or competition, stress, and disturbance, or their interactions? We discovered four patterns that may be predictive of what future PSF studies conducted under more realistic conditions might reveal. First, relatively little is known about how PSF responds to environmental stress and disturbance compared to plant-plant competition. Second, specific types of competition enhanced negative effects of soil microbes on plant growth, and specific environmental stressors enhanced positive effects of soil microbes on plant growth. Third, whether PSF experiments are conducted in the field or greenhouse can change plant growth responses. And, fourth, how the soil conditioning phase is conducted can change plant growth responses. With more detail than previously shown, these results confirm that environmental context writ large can change plant growth responses in PSF experiments. These data should aid theory and predictions for conservation and restoration applications by showing the relative importance of competition, stress, and disturbance in PSF studies over time. Lastly, these data demonstrate how variation in experimental methods can alter interpretation and conclusions of PSF studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa ( Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Longitudinal genome-wide association study reveals early QTL that predict biomass accumulation under cold stress in sorghum

Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy due to its high biomass yields. However, early growth phases of sorghum are sensitive to cold stress, limiting its planting in temperate environments. Cold adaptability is crucial for cultivating bioenergy and grain sorghum at higher latitudes and elevations, or for extending the growing season. Identifying genes and alleles that enhance biomass accumulation under early cold stress can lead to improved sorghum varieties through breeding or genetic engineering. We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP includes diverse accessions with dense genotyping and varied racial, geographical, and phenotypic backgrounds. Daily, non-destructive imaging allowed temporal analysis of growth-related traits and water use efficiency (WUE). A genome-wide association study (GWAS) was performed to identify genomic intervals and genes associated with cold stress response. The GWAS identified transient quantitative trait loci (QTL) strongly associated with growth-related traits, enabling an exploration of the genetic basis of cold stress response at different developmental stages. This analysis of daily growth traits, rather than endpoint traits, revealed early transient QTL predictive of final phenotypes. The study identified both known and novel candidate genes associated with growth-related traits and temporal responses to cold stress. The identified QTL and candidate genes contribute to understanding the genetic mechanisms underlying sorghum's response to cold stress. These findings can inform breeding and genetic engineering strategies to develop sorghum varieties with improved biomass yields and resilience to cold, facilitating earlier planting, extended growing seasons, and cultivation at higher latitudes and elevations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Validating the Use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields

Probing the stress state using a high density of measurement points is time intensive and presents a limitation for what is experimentally feasible. Alternatively, individual strain fields used for determining stresses can be reconstructed from a subset of points using a Gaussian process regression (GPR). Results presented in this paper evidence that determining stresses from reconstructed strain fields is a viable approach for reducing the number of measurements needed to fully sample a component’s stress state. The approach was demonstrated by reconstructing the stress fields in wire-arc additively manufactured walls fabricated using either a mild steel or low-temperature transition feedstock. Effects of errors in individual GP reconstructed strain maps and how these errors propagate to the final stress maps were assessed. Implications of the initial sampling approach and how localized strains affect convergence are explored to give guidance on how best to implement a dynamic sampling experiment.

36 MATERIALS SCIENCE↗