Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “fitting”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Constraint-dependent CTOA determination for stable ductile crack growth

The crack tip opening angle (CTOA) has been used as a reliable fracture toughness to characterize stable crack growth for thin-wall structures in low-constraint conditions. Recently, it is found that CTOA can also be utilized as a robust fracture parameter to describe the arrest fracture toughness for gas transmission pipelines in ductile steels. For better understanding the concept of CTOA, this paper presents a brief review on the CTOA definitions and its test methods. And then, four CTOA models are developed for determining the CTOA toughness using conventional single edge notched bend (SENB) specimens, including the load–displacement linear fit model, the logarithmic load–displacement linear fit model, the stable tearing energy model, and the J-differentiation model. Here fracture test data from SENB specimens in A285 carbon steel are employed to evaluate the proposed CTOA models. The results show that these CTOA models can determine either identical or comparable critical CTOA values for stable ductile crack growth using the SENB specimens. A constraint-corrected CTOA resistance curve and a constraint-corrected critical CTOA equation are also obtained for A285 carbon steel.

42 ENGINEERING↗
DOE OSTI2020

The direct and indirect effects of copper on vector-borne disease dynamics

Metal pollution is a growing concern that affects the health of humans and animals globally. Copper is an essential insect micronutrient required for respiration, pigmentation and oxidative stress protection but can also act as a potentially toxic trace element. While several studies have focused on the negative fitness effects of copper on the aquatic larvae of mosquitoes, the effects of larval copper exposure on adult mosquito fitness (i.e., survival and fecundity) and their ability to transmit parasites (i.e., vector competence) remains unclear. Here, using a well-studied model vector-parasite system, the mosquito Aedes aegypti and parasite Dirofilaria immitis, we show that sublethal copper exposure in larval mosquitoes alters adult female fecundity and vector competence. Specifically, mosquitoes exposed to copper had a hormetic fecundity response and mosquitoes exposed to 600 μg/L of copper had significantly fewer infective parasite larvae than control mosquitoes not exposed to copper. Therefore, exposure of mosquito larvae to copper levels far below EPA-mandated safe drinking water limits (1300 μg/L) can impact vector-borne disease dynamics not only by reducing mosquito abundance (through increased larval mortality), but also by reducing parasite transmission risk. Our results also demonstrated that larval copper is retained through metamorphosis to adulthood in mosquitoes, indicating that these insects could transfer copper from aquatic to terrestrial foodwebs, especially in urban areas where they are abundant. To our knowledge this is the first study to directly link metal exposure with vector competence (i.e., ability to transmit parasites) in any vector-parasite system. Additionally, it also demonstrates unequivocally that mosquitoes can transfer contaminants from aquatic to terrestrial ecosystems. These results have broad implications for public health because they directly linking contaminants and vector-borne disease dynamics, as well as linking mosquitoes and contaminant dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Neural-based time series forecasting of loss of coolant accidents in nuclear power plants

During the last few years, deep learning in neural networks has demonstrated impressive successes in the areas of computer vision, speech and image recognition, text generation, and many others. However, sensitive engineering areas such as nuclear engineering benefited less from these efficient techniques. In this work, deep learning expert systems are utilized to model and predict time series progression of a design-basis nuclear accident, featuring a loss of coolant accident. Two major findings are accomplished in this work. First, the ability to train expert systems with high accuracy, which could help nuclear power plant operators to figure out plant responses during the accident. Second, building fast, efficient, and accurate deep models to simulate nuclear phenomena, which could be valuable to nuclear computational science. In this work, large amount of time series data is obtained from simulation tools by simulating different conditions of the base-case/nominal accident scenario. Four critical outputs/responses are monitored during the accident (e.g. temperature, pressure, break flow rate, water level). Two approaches are adopted in this work. The first approach is to use feedforward deep neural networks (DNN) to fit all time steps and outputs in a single model. The second approach is to use long short-term memory (LSTM) to fit all time steps together for each reactor response separately. Both DNN and LSTM demonstrate very good performance in predicting the test and base-case scenarios, with accuracy as low as 92% and as high as 99%, where these test scenarios are unknown to the expert systems and are not included in the model training. In addition, both approaches demonstrate a significant reduction in computational costs, as the deep expert system is able to accurately predict the accident 100,000 times faster than the original simulation tool. Given sufficient data, the methodology adopted in this study demonstrates that DNN/LSTM expert systems can be used as a decision support system to model advanced time series phenomena within nuclear power plants with high accuracy and negligible computational costs.

42 ENGINEERING↗
DOE OSTI2020

Reexamining supercritical gas adsorption theories in nano-porous shales under geological conditions

Adsorption is an important phenomenon in surface chemistry, especially for nano-porous shales. In the shale gas-in-place, adsorbed gas could contribute up to 85%. However, adsorption is hard to quantitatively characterize due to different adsorption mechanisms, patterns, surfaces, and pore sizes. Moreover, key thermodynamic parameters, such as the enthalpy of adsorption, are challenging to determine due to uncertainties in adsorbed gas densities used in constructing absolute isotherms. In this paper, we revisit the Brunauer, Emmett, and Teller (BET) model, analytically simplify Ono-Kondo (OK) models for subsurface shales, and compare commonly used mono- and multilayer adsorption models (e.g., Langmuir, supercritical Dubinin-Radushkevich (SDR), supercritical BET (SBET), and simplified OK (OKs) models) with recently proposed pressure-dependent adsorption densities to develop a practical and reliable methodology that can be used in the supercritical state, typical for subsurface black shale conditions.Three independent data sets were used for nitrogen and methane adsorption isotherms at different temperatures. Furthermore, we demonstrate that adsorption predicted by the SDR model is comparable or lower than that predicted by the SBET model, but higher than the amounts predicted by Langmuir and OK models. The nitrogen BET method tends to underestimate the accessible SSA for methane. Measurement of isosteric heat of adsorption is suggested instead of the experimental fitting method, due to the significant difference between the calculated results by two commonly used methods. Experimental fitting and simulation methods are also briefly reviewed to guide future research on shale gas adsorption.

58 GEOSCIENCES↗
DOE OSTI2022

High manganese redox variability and manganate predominance in temperate soil profiles as determined by X-ray absorption spectroscopy

Manganese speciation is a key to understanding the fate of contaminants, nutrients, and organic matter in soils. To date, quantification of Mn species in bulk soils has been performed mainly by sequential extraction methods and rarely supported by spectroscopic analysis. In order to obtain quantitative information on the Mn species inventory of soils, we investigated 46 soil horizons (<2-mm fraction, 45.1–2,280 mg/kg Mn) of nine typical Central European soils (Cambisols, Chernozems, Luvisols, Podzol, Stagnosol) by chemical Mn analyses and Mn K-edge X-ray absorption spectroscopy, and related speciation results to major soil properties. Amounts of Mn 2+ , Mn 3+ , and Mn 4+ and the average oxidation state of Mn were evaluated by linear combination fitting (LCF) of X-ray absorption near edge structure (XANES) spectra. Additionally, we used extended X-ray absorption fine structure (EXAFS) spectroscopy to identify and quantify major Mn species. For this, EXAFS spectra of 20 organic and mineral soil samples from five soils (Cambisols, Chernozem, Luvisol) were analyzed by LCF and shell fitting. XANES analyses revealed a high Mn redox variability in organic surface layers, with Mn 2+ being most abundant (≤100%, $\overline{x}$ = 54%), followed by Mn 3+ (≤80%, $\overline{x}$ = 32%) and Mn 4+ (≤55%, $\overline{x}$ = 14%). Mineral soil horizons contained significantly less Mn 2+ (≤56%, $\overline{x}$ = 23%), about equal quantities of Mn 3+ (≤68%, $\overline{x}$ = 31%), and were enriched in Mn 4+ (≤89%, $\overline{x}$ = 46%). EXAFS analyses implied the presence of six major Mn species groups: manganates, organically complexed Mn, Mn(III) oxyhydroxides, silicate-bound Mn, Mn oxides without tunnel- or layer structure, and physisorbed Mn. In litter horizons, Mn was mainly present in organic complexes (58–91%, $\overline{x}$ = 78%) and as physisorbed Mn (≤15%), but individual horizons also comprised manganates, Mn(III) oxyhydroxides, and silicate-bound Mn. Manganates, likely mixtures of phyllomanganates with hexagonal layer symmetry and tectomanganates, dominated in all mineral soil horizons (37–94%, $\overline{x}$ = 67%). Correlation analysis showed that manganates dissolve completely during dithionite-citrate and acid ammonium oxalate extractions, and suggested that Mn 4+ -rich manganates preferentially form under less acidic soil conditions, partly by oxidation of organically complexed Mn(II), and that they are enriched in the soil clay fraction. Mineral soil horizons also contained minor quantities of organically complexed Mn (≤39%, $\overline{x}$ = 11%), silicate-bound Mn (≤30%, $\overline{x}$ = 8%), Mn(III) oxyhydroxides (≤37%, $\overline{x}$ = 7%), Mn oxides without tunnel- or layer structure (≤18%, $\overline{x}$ = 5%), and physisorbed Mn (≤14%, $\overline{x}$ <1%). The detection of Mn(III) oxyhydroxides such as feitknechtite (β-MnOOH) or groutite (α-MnOOH) as well as the spinel hausmannite (Mn 3 O 4 ) in acidic soils is remarkable, since their formation is normally linked to neutral or alkaline pH conditions. Minor contributions of silicate-bound Mn indicate the release of Mn from primary minerals already at early stages of soil formation, and low concentrations of physisorbed Mn suggest that exchangeable Mn is rapidly converted into manganates in oxic soils. In conclusion, the predominance of manganates in mineral soils has far-reaching implications for the functioning of soils and biogeochemical element cycles, as these minerals play an important role in metal binding, plant nutrition, and redox-related processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Measurements of the thermal conductivity of reference liquids using a modified transient hot-wire needle probe

Many power generation processes feature some type of working fluid that plays a critical role in the transfer of heat throughout the system. To optimize thermal efficiencies, an accurate characterization of the temperature-dependent thermal conductivity of the fluid is needed. Herein, this study develops a time-domain Modified Transient Hot-wire Needle Probe to overcome phenomena that have impaired traditional measurement techniques when the fluid is both corrosive and at an elevated temperature. First, the physical design of the instrument is presented to demonstrate features that limit interference from corrosion, electrical conduction, and convective and radiative heat transfer. Next, a governing equation for 1D (radial) heat conduction is fully developed using the thermal quadrupoles technique. A finite-element study is performed for validation. A sensitivity analysis is done to assess the time-dependent influence of critical parameters in the governing equation for several samples. Finally, thermal conductivity measurements are presented for seven different liquid substances by fitting the thermal model to experimental data across a range of temperatures. Reference correlations are included for comparison. The sample thermal conductivity and ambient temperature of the experimental conditions range from 0.125–16.5$\frac{W}{m·K}$ and 10–400°C, respectively. The total uncertainty, comprised of both the experimental design and fitting process, of all measurements is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Analytical solution and parameter estimation for heat of wetting and vapor adsorption during spontaneous imbibition in tuff

An analytical expression is derived for the thermal response observed during spontaneous imbibition of water into a dry core of zeolitic tuff. Sample tortuosity, thermal conductivity, and thermal source strength are estimated from fitting an analytical solution to temperature observations during a single laboratory test. Here, the closed-form analytical solution is derived using Green's functions for heat conduction in the limit of “slow” water movement; that is, when advection of thermal energy with the wetting front is negligible. The solution has four free fitting parameters and is efficient for parameter estimation. Laboratory imbibition data used to constrain the model include a time series of the mass of water imbibed, visual location of the wetting front through time, and temperature time series at six locations. The thermal front reached the end of the core hours before the visible wetting front. Thus, the predominant form of heating during imbibition in this zeolitic tuff is due to vapor adsorption in dry zeolitic rock ahead of the wetting front. The separation of the wetting front and thermal front in this zeolitic tuff is significant, compared to wetting front behavior of most materials reported in the literature. This work is the first interpretation of a thermal imbibition response to estimate transport (tortuosity) and thermal properties (including thermal conductivity) from a single laboratory test.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A model to separate conduction and radiation in high temperature laser flash measurements for semi-transparent materials

Laser flash analysis (LFA) is a widely used technique in the scientific and industrial communities for measuring the thermal diffusivity and conductivity of materials. However, traditional fitting methods based solely on heat conduction do not account for radiation heat transfer in transparent and semi-transparent materials, which becomes significant at high temperatures. In this study, we have developed a coupled radiation-conduction model that considers the optical properties of materials to accurately extract thermal diffusivity from LFA measurements. We conducted LFA measurements on fused silica glass samples of varying thicknesses and within the temperature range of 25 to 1000 °C and fitted the data with the model. Since the coupled model requires optical properties as input parameters, which are often unavailable for new materials, we have also proposed a modified transparent model. Compared to the coupled model, results from the modified transparent model generally overestimate thermal conductivity, but the errors are acceptable in silica glass with small thickness. Here, we also investigated the applicability of the modified transparent model with materials of different optical properties.

14 SOLAR ENERGY↗
DOE OSTI2023

Training material models using gradient descent algorithms

High temperature design requires accurate constitutive models to describe material inelastic deformation and failure behavior. Oftentimes, calibrating accurate models devolves into the problem of fitting the model parameters against experimental test data. Here, we present the pyopmat package, an open source framework for calibrating constitutive models against experiment data subjected to various loading conditions using machine learning techniques. The package calculates the exact gradient of the model response with respect to the parameters using a combination of automatic differentiation and the adjoint method. Given this exact gradient, we compare the performance of several gradient-based optimization techniques in fitting realistic constitutive models against data. Here, we demonstrate the efficiency and accuracy of our package through example problems using both synthetic data, generated using known parameter sets, under monotonic and cyclic loading conditions and also with an example applying the techniques developed here to actual high temperature creep-fatigue test data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A generalized power-law criterion for rocks based on Mohr failure theory

Nonlinearity of Mohr envelopes confirmed by past laboratory test data can be of considerable importance in theoretical interpretation of rock strength behaviors and many practical applications. Current nonlinear failure criteria are introduced with parameters to empirically fit test data, and the physical and mechanical meanings of these fitting parameters are often not known. Predicted strengths by theoretical criteria (e.g., Griffith criterion) generally do not agree well with test data. Considering the nonlinear properties of a Mohr envelope, a nonlinear failure criterion in a generalized power-law form is derived in this paper based on strength magnitude coefficient (a) and failure envelope curvature coefficient (n) which are expressed in terms of uniaxial tensile strength, uniaxial compressive strength, and angle of internal friction. Test data on granite, marble, dolomite, and andesite from published literature were chosen to test the performance of the proposed criterion along with Griffith and Hoek-Brown criteria. Statistical analysis was performed to evaluate the application of different criteria in predicting the strength of rocks. In addition, some Griffith-typed criteria are mathematically shown to be the special cases of the proposed criterion. The proposed and Hoek-Brown criteria have similar power-law forms with a significant difference in the coefficient functions that govern the shear strength magnitude of rock. The different tensile and compressive failure mechanisms are also investigated from the perspective of the relationship between the uniaxial tension Mohr circle and the proposed failure envelope.

58 GEOSCIENCES↗
DOE OSTI2022

Logistic Regression in Clinical Studies

• A logistic regression model is used when the outcome of interest is binary. The term “logistic” refers to the underlying “logit” (log odds) function that is used to model the binary outcome. • Odds ratios are produced from a logistic regression model and have a useful interpretation. • Tips, tricks and concepts used to fit logistic regression models are similar to those used in linear regression models. • Modeling building that is knowledge-based rather than automatic is preferred in most applications of logistic regression. • A logistic regression model that is overparameterized (ie, too many variables for too few events) can result in odds ratios that are implausibly large and confidence intervals that are wide and uninterpretable. These types of “overfitted” models should be avoided. • Logistic regression models can be fit using most standard statistical software.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗
DOE OSTI2020

Oxide-catalyzed self- and cross-condensation of cycloketones. Kinetically relevant steps that determine product distribution

Metal oxides with acid-base properties can be used to catalyze aldol condensation and potentially obtain valuable chemicals from biomass-derived oxygenates. Understanding the reaction mechanisms could enable the development of effective catalysts with controllable selectivity. In this work, we investigate the reaction parameters that affect the kinetics and product distribution of self- and cross-aldol condensation of cyclopentanone (CPO) and cyclohexanone (CHO) over CeO 2 and ZrO 2 catalysts by combining detailed analysis of experiments and DFT calculations. It is well-known that either the deprotonation of an α-C–H that generates an enolate or the C–C coupling that produces the dimers can be rate-limiting step. Indeed, the detailed kinetics analysis shows that the observed data can be fitted by unimolecular or bimolecular Langmuir-Hinshelwood models. Specifically, on the ZrO 2 catalyst, the unimolecular α-C–H activation is the rate limiting step for the CPO self-condensation, while the bimolecular C–C coupling limits the CHO self-condensation. By contrast, on CeO 2 , the bimolecular C–C coupling step seems to be rate-limiting for both CPO and CHO self-condensation reactions. The adsorption parameters derived from kinetics fitting indicate that when the two reactants are co-fed, the surface is preferentially covered by CHO. So, the condensation rate of [CPO]-activated products ([CPO]CPO + [CPO]CHO) decreases in the presence of CHO, due to the competitive adsorption. However, despite a higher surface coverage, CHO is not an effective electrophile because it imposes stronger steric constraints to the formation of the C–C bond than CPO. Therefore, for a given enolate, the product distribution shows that [CPO]CPO > [CPO]CHO and, similarly [CHO]CPO > [CHO]CHO. Likewise, the yields of [CPO]- and [CHO]-activated products in mixed CPO/CHO feeds are similar because the higher surface coverage and stability of the [CHO] enolate is counterbalanced by the inhibition of C–C coupling by steric constraints when CHO is involved. In summary, the overall rank of products observed experimentally can be explained in terms of a combination of the following effects: relative surface coverage of the reactants, steric constraints for the C–C coupling, stability of the enolate, and effectiveness of the electrophile to accept an electron.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An arbitrarily high-order three-dimensional Cartesian-grid method for reconstructing interfaces from volume fraction fields

Here Tthis work describes a newly developed, arbitrarily high-order Cartesian-grid method for reconstructing material interfaces from a volume fraction field. The method begins by identifying all of the grid cells in the volume fraction field that are intersected by the interface and need to be approximated by the reconstruction scheme. Finite-differences are used to calculate the gradient of the volume fraction field and provide an estimate of the surface normal in all of the interfacial grid cells. Groups of connected grid cells are then identified which all have the same dominant component of the normal vector. This grouping by orientation determines the proper dependent variable to use in the surface reconstruction (e.g. for a 2D curve, this step determines if the surface will be approximated by a function of x or y). A cumulative integral over the surface is constructed and fit using b-splines for two-dimensional problems or tensor-product b-splines for three-dimensional problems. This construction allows for the interface to be recovered through application of the second fundamental theorem of calculus. Fitting the cumulative integral with $\mathscr{N}$ th-order b-splines (or tensor-product b-splines) yields an ($\mathscr{N}$-1) th-order convergence rate of the interface shape. Differentiation of the b-spline interface function(s) allows for the high-order approximation of the normal vector and curvature to be obtained directly anywhere along b-spline. Together, the proposed reconstruction technique can achieve arbitrarily high mesh convergence rates. Validation tests are presented with mesh convergence rates ranging from fourth- to tenth-order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Efficiency and mechanisms of Sb(III/V) removal by Fe-modified biochars using X-ray absorption spectroscopy

Fe-modified biochars (FeBC) are effective antimony (Sb) removal materials; however, the removal mechanisms require further investigation. In this study, aqueous Sb(III) and Sb(V) removal by FeBC (300, 600, and 900 °C) was evaluated, with the adsorption mechanisms investigated using X-ray absorption spectroscopy (XAS). Screening results (based on removal efficiencies) using different types of FeBC indicated the 900 °C FeCl3- modified biochar (FeCl3BC900) achieved the best Sb(III/V) removal performance. The kinetics of the Sb(III/V) removal process were best fitted by a pseudo-second-order model. Additionally, the isothermal results were described by Langmuir and Redlich-Peterson models. Aqueous analysis and X-ray absorption near-edge structure data fitting indicated Sb(III) was oxidized to Sb(V) in the Sb(III)-spiked system, and the oxidation extent increased with increasing pyrolysis temperature. The oxidation process rapidly occurred in both the solution and biochar. No Sb(V) was reduced to Sb(III) in the Sb(V)-spiked system. The XAS results of the isothermal experiment indicated the oxidation capacity of FeCl3BC900 was limited for high initial Sb(III) concentrations. The SbFe1 and Sb-Fe2 bonding distances were 3.05–3.10 and 3.47–3.54 Å, respectively, indicating inner-sphere complexes were formed during the Sb(III/V) removal processes. The Sb(III/V) removal mechanisms included electrostatic adsorption, inner-sphere complexes, and coprecipitation. Oxidation was also involved in Sb(III) removal.

Antimony↗
DOE OSTI2022

Cosmology intertwined: A review of the particle physics, astrophysics, and cosmology associated with the cosmological tensions and anomalies

The standard Λ Cold Dark Matter (ΛCDM) cosmological model provides a good description of a wide range of astrophysical and cosmological data. However, there are a few big open questions that make the standard model look like an approximation to a more realistic scenario yet to be found. In this paper, we list a few important goals that need to be addressed in the next decade, taking into account the current discordances between the different cosmological probes, such as the disagreement in the value of the Hubble constant H 0 , the σ 8 – S 8 tension, and other less statistically significant anomalies. While these discordances can still be in part the result of systematic errors, their persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the necessity for new physics or generalisations beyond the standard model. In this paper, we focus on the 5.0 σ tension between the Planck CMB estimate of the Hubble constant H 0 and the SH0ES collaboration measurements. After showing the H 0 evaluations made from different teams using different methods and geometric calibrations, we list a few interesting new physics models that could alleviate this tension and discuss how the next decade's experiments will be crucial. Moreover, we focus on the tension of the Planck CMB data with weak lensing measurements and redshift surveys, about the value of the matter energy density Ω m , and the amplitude or rate of the growth of structure ( σ 8 , f σ 8 ). We list a few interesting models proposed for alleviating this tension, and we discuss the importance of trying to fit a full array of data with a single model and not just one parameter at a time. Additionally, we present a wide range of other less discussed anomalies at a statistical significance level lower than the H 0 – S 8 tensions which may also constitute hints towards new physics, and we discuss possible generic theoretical approaches that can collectively explain the non-standard nature of these signals. Finally, we give an overview of upgraded experiments and next-generation space missions and facilities on Earth that will be of crucial importance to address all these open questions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

For this work, we numerically evaluated photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively) on stream corridor transport. Correctly separating HSZ and SSZ effects is critical to estimating the hydro-biogeochemical function of a stream because HSZs and SSZs expose solutes to significantly different biogeochemical conditions, like sunlight exposure, microbial processes, and oxygen availability. Our numerical experiments used a multiscale river-corridor transport model implemented in the ATS code, which accommodates multiple storage zones with distinct travel time distributions and biogeochemical reactions. For parameter inferences, we used Bayesian inverse modeling. We found that breakthrough curves for photo-decaying tracers from day and night injection can delineate surface and hyporheic transient storage contributions, but only when interpreted jointly through a two-storage zone model. Numerical experiments that used only daytime injection or interpreted breakthrough curves with a single storage zone model yielded good fit to breakthrough curves, but parameter estimates were biased and controlling processes misattributed, examples of good model fits for the wrong reasons. Using those biased parameter estimates in reactive transport simulations resulted in significantly different projections of denitrification, which underscores the potential for stream function to be mischaracterized if tracer tests are interpreted through an inappropriately simplified model for transient storage. More generally, this study highlights the role of modeling in evaluating the experimental design and identifying the potential of system mischaracterization and its implications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression

Here, an interpretable machine learning method, physics-informed genetic programming-based symbolic regression (P-GPSR), is integrated into a continuum thermodynamic approach to developing constitutive models. The proposed strategy for combining a thermodynamic analysis with P-GPSR is demonstrated by generating a yield function for an idealized material with voids, i.e., the Gurson yield function. First, a thermodynamic-based analysis is used to derive model requirements that are exploited in a custom P-GPSR implementation as fitness criteria or are strongly enforced in the solution. The P-GPSR implementation improved accuracy, generalizability, and training time compared to the same GPSR code without physics-informed fitness criteria. The yield function generated through the P-GPSR framework is in the form of a composite function that describes a class of materials and is characteristically more interpretable than GPSR-derived equations. The physical significance of the input functions learned by P-GPSR within the composite function is acquired from the thermodynamic analysis. Fundamental explanations of why the implemented P-GPSR capabilities improve results over a conventional GPSR algorithm are provided.

42 ENGINEERING↗