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The abstracts included in this document are: Responsiveness, Modernization, and Radiography Test at the Centrifuge Test Facility; LANL Hostile Blast Testing Capability Development; Digital Image Correlation Measurement of B61 Center Case Fragmentation Test; and Collaborative Analysis Testing Techniques (CATT) Phase 1.
Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.
ABSTRACT The integrated Sachs–Wolfe (ISW) effect probes the late-time expansion history of the Universe, offering direct constraints on dark energy. Here, we present our measurements of the ISW signal at redshifts of $\bar{z}=0.35$, 0.55, and 0.68, using the cross-correlation of the Planck cosmic microwave background temperature map with ∼0.5 million luminous red galaxies (LRGs) selected from the VST ATLAS survey. We then combine these with previous measurements based on WMAP and similar SDSS LRG samples, providing a total sample of ∼2.1 million LRGs covering ∼12 000 deg2 of sky. At $\bar{z}=0.35$ and $\bar{z}=0.55$, we detect the ISW signal at 1.2σ and 2.3σ (or 2.6σ combined), in agreement with the predictions of lambda cold dark matter (ΛCDM). We verify these results by repeating the measurements using the BOSS LOWZ and CMASS, spectroscopically confirmed LRG samples. We also detect the ISW effect in three magnitude limited ATLAS + SDSS galaxy samples extending to z ≈ 0.4 at ∼2σ per sample. However, we do not detect the ISW signal at $\bar{z}=0.68$ when combining the ATLAS and SDSS results. Further tests using spectroscopically confirmed eBOSS LRGs at this redshift remain inconclusive due to the current low sky coverage of the survey. If the ISW signal is shown to be redshift dependent in a manner inconsistent with the predictions of ΛCDM, it could open the door to alternative theories such as modified gravity. It is therefore important to repeat the high-redshift ISW measurement using the completed eBOSS sample, as well as deeper upcoming surveys such as DESI and LSST.
Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.
In order to improve the accuracy and capabilities of neutron multiplicity counting, additional quantifiable information is needed in order to address the assumptions that are present in the point model. Extracting and utilizing higher order moments (Quads and Pents) from the neutron pulse train represents the most direct way of extracting additional information from the measurement data to allow for an improved determination of the physical properties of the item of interest. The extraction of higher order moments from a neutron pulse train required the development of advanced dead time correction algorithms which could correct for dead time effects in all of the measurement moments in a self-consistent manner. In addition, advanced analysis algorithms have been developed to address specific assumptions that are made within the current analysis model, namely that all neutrons are created at a single point within the item of interest, and that all neutrons that are produced within an item are created with the same energy distribution. This report will discuss the current status of implementation and initial testing of the advanced dead time correction and analysis algorithms that have been developed in an attempt to utilize higher order moments to improve the capabilities of correlated neutron measurement techniques.
Here, we assess the performance of seven exchange–correlation functionals (some with and some without a Hubbard U correction) for their ability (i) to predict band gaps of silicon, diamond, and Li-ion battery cathode materials, (ii) to localize hole polarons and predict delithiation energies in Li-ion battery cathode materials, and (iii) to predict transition levels of charge carriers of doped silicon and diamond. Both local and hybrid exchange–correlation functionals were tested. The local functionals tend to underestimate band gaps and delocalize polarons. The hybrid functionals very often give a good description of both properties, but they may not be practical for calculations involving large unit cells, large ensembles, or dynamics, and therefore a local functional with a Hubbard U correction is often used (giving the method called DFT+U), where the value of a parameter U is adjusted according to the system and the property being investigated. Keeping in mind the importance of computational cost and the undesirability of having to adjust an empirical parameter for each system or property of interest, we recently developed a local functional, namely HLE17, to try to accurately predict band gaps and excitation energies, and we validated it using mostly main-group solids and molecules. Here we test the performance of HLE17 for its ability to predict band gaps and localize polarons in other solid-state materials, and we compare its performance to that of popular local functionals (PBE, PBEsol, and TPSS), a range-separated hybrid functional with screened exchange (HSE06), and DFT+U. We find that HLE17 predicts more accurate band gaps than other local functionals and can localize holes as polarons, which other local functionals usually fail to do, and for a number of cases it is comparable in performance quality to Hubbard-corrected functionals without the need for system-specific parametrization and to hybrid functionals without the high cost. Because HLE17 does not predict accurate lattice constants, we use the single-point method of quantum chemistry, where the geometry is optimized with one functional and the band gap is calculated with HLE17, or we perform calculations with the lattice constants obtained by TPSS and both the fractional intracell coordinates and the electronic structure obtained by HLE17 (a new method denoted HLE17\\TPSS). In particular, we performed calculations by HLE17//TPSS, HLE17//HSE06, HLE17//DFT+U, and HLE17\\TPSS, and these methods usually agree well with each other and give values similar to experiment.
Environmental exposure to crude oil through seepage and spillage poses risks to the immediate environment and the broader ecosystem as areas along the oil distribution path are affected by the influx of crude petroleum as well as the environmental, economic, and civil unrest that accompanies it. There is a large financial burden associated with the lost resources, including the cost of rehabilitation, and the affected sources of revenue for communities affected by oil spills. As such, it is crucial to determine the responsible parties. This work outlines an environmental forensics approach to determining the source of an un-weathered crude oil sample. The researchers employed solid phase microextraction coupled with gas chromatography mass spectrometry (SPME-GC-MS) to capture and analyze the gaseous components emitted by crude oil samples sourced from five locations. Samples were analyzed using Spearman's rank correlation and 3D covariance analysis. Both chemometric approaches yielded optimal performance results with no misclassifications, true positive rate (TPR) = 100 % and false positive rate (FPR) = 0 %. The similarity metrics calculated by each test noted clear delineations between the values of same-source and differently sourced samples. The Spearman's rank correlation test and 3D covariance calculations both demonstrated the ability to correctly identify sample source origin in this dataset. Finally, the authors outline an approach to the future application of these tests and suggest their joint use in future crude oil sourcing endeavors.
Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further understanding of the relationship between microstructure and fracture properties of high-strength 6000-series alloys. This work started with microstructural characterization in both mesoscale and nanoscale and bending performance characterization of AA6111 HS2-T6 alloy at Ford, the MMN framework was applied to this alloy to simulate 3-point VDA bending. From the results of the macro-modeling of 3-point VDA bending, the critical region of fracture was identified, and the region geometry was used to construct the micro-model. The fracture criterion of micron-scale precipitates and aluminum matrix which contains submicron and nano particles (AL-SMP-NP) in the micro-model was calibrated and validated by comparing simulated and measured bending results. With the AL-SMP-NP fracture strain obtained, the fracture strain of Al-matrix containing nano particles (ALNP) will similarly be determined by a submicron scale-model using an edge-constrained FE modeling approach developed by Hu et al. With the ALNP fracture strain obtained, the fracture strain of Al-matrix containing no particles will similarly be determined by a nano scale-model using an edge-constrained FE modeling approach. After the MMN framework is built and fracture criterion calibrated, nano-model FE simulations with virtual microstructures was performed to obtain a reduced order model (ROM) of the fracture criterion of the ALNP as a function of volume fraction, size, and distribution of the nanoparticle. This nano→submicron→micro modeling part allows exploration of the influence of different material nanostructures from different process conditions on the bending properties within the multiscale bending simulation framework and the ROM of material bendability as a function of nanoparticle size and shape was established. This obtained reduced order model (ROM) could help guide the design and selection of materials to improve existing SPR process models that could replace trial-and-error rivet/die selection and help to design new rivet/die combinations capable of robustly joining new higher strength 6000 5 series alloys in automotive body structures. This would enable lightweighting of Ford vehicles leading to greater fuel efficiency and reduce manufacturing time and energy.
Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and spaceborne precipitation radars and three cloud-resolving models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.
Purpose: This study aims to determine whether contrast-enhanced (CE)-magnetic resonance imaging (MRI) is comparable to CE-computed tomography (CT) for estimation of split renal function (SRF). For this purpose, two different kidney volumetry methods, the renal cortex volumetry (RCV) and modified ellipsoid volume (MELV), are compared for both acquisition types (CT vs. MRI) with regard to accuracy and reliability, subsequently referred to as RCV{sub CT}/RCV{sub MRI} and MELV{sub CT}/MELV{sub MRI}. Methods: This retrospective study included 29 patients (18 men and 11 women; mean age 62.8 ± 12.4 years) who underwent CE-MRI and CE-CT of the abdomen within a period of 3 months. Two independent readers (R1/R2) performed RCV and MELV in all datasets with corresponding semiautomated software tools. RCV was performed with datasets in the arterial phase and MELV in the venous phase. Statistics were calculated using one-way ANOVA, two-tailed Student’s t test, Pearson´s correlation, and Bland–Altman plots with p ≤ 0.05 being considered statistically significant. Results: In all datasets, SRF was almost identical for both volumetry methods with a mean difference of < 1%. Bland–Altman analysis comparing RCV in CT and MRI showed very good agreement for R1/R2. Interreader agreement was strong for RCV{sub CT} and good for RCV{sub MRI} (r = 0.89; r = 0.69). MELV{sub CT/MRI} interreader agreement was only moderate (r = 0.54; r = 0.50) with a high range of values. Intrareader agreement was excellent for all measurements, except MELV{sub MRI} which showed a high mean bias and range of values (RCV{sub CT}: r = 0.93, RCV{sub MRI}: r = 0.98, MELV{sub CT}: r = 0.89, MELV{sub MRI}: r = 0.54). Conclusion: Renal volumetric estimates of SRF are almost as accurate and reliable with CE-MRI as with CE-CT using RCV method. In distinction, the calculation of SRF using MELV was inferior to RCV with respect to accuracy and reliability. Thus, RCV method is recommended to estimate SRF, primarily using CT datasets. However, RCV with MRI datasets for kidney volumetry allows for comparable accuracy and reliability while sparing patients and healthy donors of unnecessary radiation exposure.
Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with C3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.
Ambient mass spectrometry is a powerful approach for rapid, high-throughput, and direct sample analysis. Due to the open-air desorption and ionization processes, random fluctuations of ambient conditions can lead to large variances in mass-spectral signals over time. The mass-spectral data also can be further complicated due to multiple analytes present in the sample, background-ion signals stemming from the desorption/ionization source itself, and other laboratory-specific conditions (e.g., ambient laboratory air, nearby hardware). Thus, background removal and analyte-ion recognition can be quite difficult, particularly in non-targeted analyses. Here, we demonstrate the use of a cross-correlation-based approach to exploit chemical information encoded in the time domain to group/categorize mass-spectral peaks from a single analysis dataset. Ions that originate from ambient (or other) background species were readily flagged and removed from spectra; the result was a decrease in mass-spectral complexity by over 70% due to the removal of these background ions. Meanwhile, analyte ions were differentiated and categorized based on their time-domain profiles. With sufficient mass resolving-power and mass-spectral acquisition rate, isolated mass spectra containing ions from the same species in a sample could be extracted, leading to a reduction in mass-spectral complexity by more than 98% in some cases. The cross-correlation approach was tested with different ionization sources as well as reproducible and irreproducible sample introduction. Software built in-house enabled fully automated data processing, which can be performed within a few seconds. Ultimately, this approach provides an additional dimension of analyte separation in ambient mass-spectrometric analyses with information that is already recorded throughout the analysis. .
Hydrologic processes interact with geomorphic patterns to create the spatial and temporal variation in riverine habitat that affects the distribution of aquatic species throughout stream networks. The process domains concept (PDC) states that longitudinally-abrupt changes in geomorphic processes along streams determine temporal patterns of natural disturbance that influence the distribution of stream organisms. Despite its potential generality, the PDC has been applied primarily to mountain streams of western North America. We tested the utility of the PDC as a conceptual framework for characterizing spatiotemporal variability in abiotic conditions and assessed the influence of process domains (PDs) on community composition of fishes and mussels along a fifth order river mainstem in the gulf coastal plain of the southeastern United States. We measured channel cross sections at three transects nested within three sites nested within three stream reaches to quantify multi-scale spatial variability in channel geomorphology along the mainstem of the Neches River, Texas, USA. Next, we modeled stage-dependent channel hydraulics to quantify temporal variability in habitat area and benthic disturbance. Lastly, we sampled fishes and mussels at each site and tested whether PDs correlate with spatial variation in taxonomic and functional community composition. Channel cross-sectional dimensions varied at the reach scale and affected the modeled temporal variability in habitat area and benthic disturbance. This interaction between channel geomorphology and disturbance regime indicated the presence of distinct PDs at the reach scale. Taxonomic composition of fishes did not differ among reaches, whereas abundance and richness of mussels were strongly reduced in the upper reach compared to the middle and lower reaches. Only slight differences in functional traits of fishes and mussels were apparent among reaches, suggesting that reach scale PDs do not influence community composition via the filtering of these functional traits. This study provides empirical evidence that the PDC is a useful framework for describing hydrogeomorphic conditions and mussel abundance and richness and can guide channel restorations in streams draining regions of low topography.
In this study, we study the effect of crystallographic orientation and applied triaxiality on the growth of intragranular voids. Two 3D full-field micromechanics methods are used, the dilatational visco-plastic fast-Fourier transform (DVP-FFT) and the crystal plasticity Finite Elements (CP-FE), both of which incorporate a combination of crystalline plasticity and dilatational plasticity. We demonstrate with several select cases that predictions of void growth from both formulations agree qualitatively. With the more computationally efficient DVP-FFT, additional effects of polycrystalline microstructure and the influence of nearest neighborhood are investigated. Crystals bearing a single intracrystalline void are studied in three types of 3D microstructural environments: isolated single crystals, individual equal-sized grains within a regular polycrystal, and individual variable sized grains within a polycrystal with grains and voids randomly located. We show that loading type plays a significant role. In strain-rate controlled conditions, voids in the hardest [111]-crystals grow the fastest in time, whereas in stress-controlled conditions, voids in the softest [100]-crystal grow the fastest in time. The analysis reveals that on average void growth is slower for the same starting orientation in the polycrystal than in the single crystal. We find that at the highest triaxiality tested that the correlation between crystal orientation and void growth rate in the polycrystal strengthens, drawing closer to that seen in the isolated single crystals. These results and model can help guide the microstructural design of polycrystalline materials with high strength and damage-tolerance in high-rate deformation.
Purpose: We examined whether rectal dose-volume histogram (DVH) parameters were associated with long-term patient-reported gastrointestinal (GI) quality of life (QOL) after conventional (70.2 GyE) or high-dose (79.2 GyE) radiation for prostate cancer. Methods and Materials: Of 64 men with localized prostate cancer alive with a minimum 7-year follow-up after treatment as part of a randomized trial with either 70.2 GyE or 79.2 GyE of external beam radiation at Massachusetts General Hospital, 56 men (88%) returned a QOL questionnaire, and 50 of those men had DVH information. The DVH parameters of the anterior rectal wall were correlated with patient-reported long-term GI QOL using Pearson correlation and t tests. Results: There was a trend toward an association between increased long-term GI dysfunction and higher V60 (p = 0.07), V65 (p = 0.06), V70 (p = 0.09), and V75 (p = 0.09). When dichotomized by their medians, a V60 > 54% (p = 0.04), V70 > 44% (p = 0.06), and V75 > 39% (p = 0.06) were associated with increased long-term GI dysfunction. There was no difference in long-term GI dysfunction between men on the conventional vs. high-dose arms (p = 0.49). Conclusions: Dose-volume histogram parameters of the anterior rectal wall were associated with long-term patient-reported GI QOL after prostate radiation, whereas the dose prescribed to the prostate was not, suggesting that DVH constraints, rather than total prescribed dose, may have the greatest impact on long-term bowel dysfunction, and therefore that continued dose escalation may be feasible if appropriate dose-volume constraints are met.
Purpose: To determine whether the accumulated dose using image guided radiation therapy is a stronger predictor of clinical outcomes than the planned dose in stereotactic body radiation therapy (SBRT) for liver metastases. Methods and Materials: From 2003 to 2009, 81 patients with 142 metastases were treated in institutional review board–approved SBRT studies (5-10 fractions). Patients were treated during free breathing (with or without abdominal compression) or with controlled exhale breath-holding. SBRT was planned on a static exhale computed tomography (CT) scan, and the minimum planning target volume dose to 0.5 cm{sup 3} (minPTV) was recorded. The accumulated minimum dose to the 0.5 cm{sup 3} gross tumor volume (accGTV) was calculated after performing dose accumulation from exported image guided radiation therapy data sets registered to the planning CT using rigid (2-dimensional MV/kV orthogonal) or deformable (3-dimensional/4-dimensional cone beam CT) image registration. Univariate and multivariate Cox regression models assessed the factors influencing the time to local progression (TTLP). Hazard ratios for accGTV and minPTV were compared using model goodness-of-fit and bootstrapping. Results: Overall, the accGTV dose exceeded the minPTV dose in 98% of the lesions. For 5 to 6 fractions, accGTV doses of >45 Gy were associated with 1-year local control of 86%. On univariate analysis, the cancer subtype (breast), smaller tumor volume, and increased dose were significant predictors for improved TTLP. The dose and volume were uncorrelated; the accGTV dose and minPTV dose were correlated and were tested separately on multivariate models. Breast cancer subtype, accGTV dose (P<.001), and minPTV dose (P=.02) retained significance in the multivariate models. The univariate hazard ratio for TTLP for 5-Gy increases in accGTV versus minPTV was 0.67 versus 0.74 (all patients; 95% confidence interval of difference 0.03-0.14). Goodness-of-fit testing confirmed the accGTV dose as a stronger dose–response predictor than the minPTV dose. Conclusions: The accGTV dose is a better predictor of TTLP than the minPTV dose for liver metastasis SBRT. The use of modern image guided radiation therapy in future analyses of dose–response outcomes should increase the concordance between the planned and delivered doses.
Synergizing wire arc-directed energy deposition (WA-DED) additive manufacturing (AM) with particle-strengthened creep strength-enhanced ferritic (CSEF) steels enables fabrication and repair of critical power-plant components. Investigations focused on fusion-welded particle-strengthened CSEF steels, such as Grade 91 steel, have linked microstructurally heterogeneous regions—forming due to heat affected zones (HAZ)—with premature failure during elevated temperature service. Fusion-based AM, including WA-DED, likewise generates microstructurally and plastically heterogeneous regions due to spatiotemporally varying thermokinetics during deposition. However, works investigating such microstructural heterogeneities, their implications for mechanical behavior, and strategies to mitigate their formation remain scarce. This work identifies microstructurally and plastically heterogeneous regions within the WA-DED-processed Grade 91 steel. Spatial microhardness variations in the as-fabricated specimen correlate with the variation in the attributes of grain, martensitic microstructure, and precipitates across the fusion zone and HAZ. Digital image correlation-enabled tensile tests performed at 500 °C revealed pronounced deformation localization and a wave-like strain distribution, with wavelength close to the melt pool depth, indicating susceptibility of the as-fabricated components to premature creep failure. Such heterogeneity in microstructural and mechanical behavior was attributed to recurring solid-state phase transformations. Subsequently, an interlayer temperature control strategy was implemented, wherein maintaining interlayer temperature above the martensitic start temperature mitigated the heterogeneous microstructural and plastic response in the as-fabricated condition. Findings open pathways to achieving deformation-localization- and creep-resistant microstructures in WA-DED fabricated particle-strengthened CSEF steel components, reducing reliance on post-welding heat treatments—conventionally required to enhance creep resistance—and enabling on-demand, short lead-time fabrication of next-generation power-plant components.