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At least 235 records · Page 13

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DOE OSTI2021

Confinement effects on the solvation structure of solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel: A first-principles study

Confinement plays an important role in determining ion transport in porous materials, which, in turn, may influence the performance of many energy storage and desalination devices. In this work, we combined density functional theory (DFT) with an implicit solvation model and ab initio molecular dynamics (AIMD) to investigate the effects of nanoconfinement on several solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel. Our DFT calculations with a solvation model indicated that cations with stronger hydration energy introduce a higher number of co-intercalated water molecules into the channel, consistent with early experimental observation obtained for MXene (2D transition metal carbide) channels. The predicted optimal water numbers for the cations were then used for AIMD simulations that explicitly include the effects of the solvent. When compared with the cations in bulk solution, our simulations showed that the hydration structure and coordination number (CN) of the solvated cations confined in the MoS 2 channel can be significantly altered. Further, we found that larger cations with weaker hydration energy (K + , Rb + , and Cs + ) exhibited a distinctive CN decrease under confinement, while smaller cations (Li + and Na + ) retained a similar hydration shell as in the bulk solution. More specifically, the hydration shell of large cations (K + , Rb + , and Cs + ) in MoS 2 showed similar features of the coordination angle to the bulk, which suggests the partially broken hydration shell with no geometry change under confinement. Our simulations provided insights into the change of the hydration structure of alkaline metal cations under confinement, which may have important implications on their transport in the 1T-MoS 2 channel.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles

Conventional physics-based modeling is a time-consuming bottleneck in control design for complex nonlinear systems like autonomous underwater vehicles (AUVs). In contrast, purely data-driven models, require a large number of observations and lack operational guarantees for safety-critical systems. Data-driven models leveraging available partially characterized dynamics have potential to provide reliable systems models in a typical data-limited scenario for high value complex systems, thereby avoiding months of expensive expert modeling time. In this work we explore this middle-ground between expert-modeled and pure data-driven modeling. We present control-oriented parametric models with varying levels of domain-awareness that exploit known system structure and prior physics knowledge to create constrained deep neural dynamical system models. We employ universal differential equations to construct data-driven blackbox and graybox representations of the AUV dynamics. In addition, we explore a hybrid formulation that explicitly models the residual error related to imperfect graybox models. We compare the prediction performance of the learned models for different distributions of initial conditions and control inputs to assess their suitability for control.

Shaw Cortez, Wenceslao E.↗

DOE OSTI2024

Simulation of gas mixture dynamics in a pipeline network using explicit staggered-grid discretization

Here we develop an explicit staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their planned lifetimes. Our computational method accommodates an arbitrary number of constituent gases with very different physical properties that may be injected into a network with significant spatiotemporal variation. In this setting, the gas flow physics are highly location- and time- dependent, so that local composition and nodal mixing must be accounted for. The resulting conservation laws are formulated in terms of pressure, partial densities and flows, and volumetric and mass fractions of the constituents. We include non-ideal equations of state that employ linear approximations of gas compressibility factors, so that the pressure dynamics propagate locally according to a variable wave speed that depends on mixture composition and density. We derive compatibility relationships for network edge boundary values that are more complex than for a homogeneous gas. The simulation method is evaluated on initial boundary value problems for a single pipe and a small network, is cross-validated with a lumped element simulation, and used to demonstrate a local monitoring and control policy for maintaining allowable concentration levels.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Theoretical Treatment of the Coriolis Effect Using Hyperspherical Coordinates, with Application to the Ro-Vibrational Spectrum of Ozone

Here, several alternative methods for the description of the interaction between rotation and vibration are compared and contrasted using hyperspherical coordinates for a triatomic molecule. These methods differ by the choice of the z -axis and by the assumption of a prolate or oblate rotor shape of the molecule. For each case, a block-structure of the rotational–vibrational Hamiltonian matrix is derived and analyzed, and the advantages and disadvantages of each method are made explicit. This theory is then employed to compute ro-vibrational spectra of singly substituted ozone; roughly, 600 vibrational states of 16 O 18 O 16 O and 16 O 16 O 18 O isomers combined, with rotational excitations up to J = 5 and both inversion parities (21600 coupled ro-vibrational states in total). Splittings between the states of different parities, so-called K -doublings, are calculated and analyzed. The roles of the asymmetric-top rotor term and the Coriolis coupling term are determined individually, and it is found that they both affect these splittings, but in the opposite directions. Thus, the two effects partially cancel out, and the residual splittings are relatively small. Energies of the ro-vibrational states reported in this work for 16 O 18 O 16 O and 16 O 16 O 18 O are in excellent agreement with literature (available for low-vibrational excitation). New data obtained here for the highly excited vibrational states enable the first systematic study of the Coriolis effect in symmetric and asymmetric isotopomers of ozone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs), especially with arbitrary initial data. We address this problem by taking advantage of recent advances in scientific machine learning and the spectral dynamically orthogonal (DO) and borthogonal (BO) methods for representing stochastic processes. The recently introduced DO/BO methods reduce the SPDE to solving a system of deterministic PDEs and a system of stochastic ordinary differential equations. Specifically, we propose two new physics-informed neural networks (PINNs) for solving time-dependent SPDEs, namely the neural network (NN)-DO/BO methods. The proposed methods incorporate the DO/BO constraints into the loss function (along with the modal decomposition of the SPDE) with an implicit form instead of generating explicit expressions for the temporal derivatives of the DO/BO modes. Hence, the NN-DO/BO methods can overcome some of the drawbacks of the original DO/BO methods. For example, we do not need the assumption that the covariance matrix of the random coefficients is invertible as in the original DO method, and we can remove the assumption of no eigenvalue crossing as in the original BO method. Moreover, the NN-DO/BO methods can be used to solve time-dependent stochastic inverse problems with the same formulation and same computational complexity as for forward problems. Furthermore, we demonstrate the capability of the proposed methods via several numerical examples, namely: (1) A linear stochastic advection equation with deterministic initial condition: we obtain good results with the proposed methods, while the original DO/BO methods cannot be applied directly in this case. (2) Long-time integration of the stochastic Burgers' equation: we show the good performance of NN-DO/BO methods, especially the effectiveness of the NN-BO approach for such problems with many eigenvalue crossings during the whole time evolution, while the original BO method fails. (3) Nonlinear reaction diffusion equation: we consider both the forward problem and the inverse problems, including very noisy initial point values, to investigate the flexibility of the NN-DO/BO methods in handling inverse and mixed type problems. Taken together, these simulation results demonstrate that the NN-DO/BO methods can be employed to effectively quantify uncertainty propagation in a wide range of physical problems, but future work should address the efficiency issue of PINNs for forward problems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

On an origin of numerical diffusion: Violation of invariance under space-time inversion

The invariant properties of the convection equation du/dt + adu/dx = 0 (where d is the partial differential operator) with respect to spatial reflection, time reversal, and space-time inversion are studied. Generally, a finite-difference analog of this equation may possess some or none of these properties. It is shown that, under certain conditions, the von Neumann amplification factor of an analog satisfies a special relation for each invariant property this analog possesses. Particularly, an analog is neutrally stable and thus free of numerical diffusion if it possesses the invariant property related to space-time inversion. It is also explained why generally (1) an upwind scheme possesses neither the invariant property related to spatial reflection nor that related to space-time inversion, and (2) an explicit scheme possesses neither the invariant property related to time reversal nor that related to space-time inversion. Extension to the viscous case and a remarkable connection between the current work and a new numerical framework for solving conservation laws are also discussed.

Chang, Sin-Chung↗

NASA NTRS2017

Impact of Coupled Radiation and Ablation on the Aerothermodynamics of Meteor Entries

A high-fidelity approach for simulating the aerothermodynamic environments of meteor entries is developed. Two primary components of this model are coupled radiation and coupled ablation. Coupled radiation accounts for the impact of radiation on the flow field energy equations, while coupled ablation explicitly models the injection of ablation products within the flow field and radiation simulations. For a meteoroid with a velocity of 20 km/s, coupled radiation reduces the stagnation point radiative heating by over 60%. For altitudes below 40 km, the impact of coupled radiation on the flow field structure is shown to be fundamentally different, as a result of the large optical thicknesses, than that seen for reentry vehicles, which do not reach such altitudes at velocities greater than 10 km/s. The impact of coupled ablation (with coupled radiation) is shown to provide at least a 70% reduction in the radiative heating relative to the coupled-radiation-only cases. This large reduction is partially the result of the low ionization energies, relative to air species, of ablation products. The low ionization energies of ablation products, such as Mg and Ca, provide strong photoionization and atomic line absorption in regions of the spectrum that air species do not. MgO and CaO are also shown to provide significant absorption. Turbulence is shown to impact the distribution of ablation products through the shock- layer, which results in up to a 100% increase in the radiative heating downstream of the stagnation point. To create a database of heat transfer coefficients the developed model was applied to a range of cases. This database considered velocities ranging from 14 to 20 km/s, altitudes ranging from 20 to 50 km, and nose radii ranging from 1 to 100 m. The heat transfer coefficients from these simulations are below 0.045 for the range of cases (with turbulence), which is significantly lower than the canonical value of 0.1.

Johnston, Christopher O.↗

DOE OSTI2025

Deep Roots Supply Reactivity and Enhance Silicate Weathering in the Bedrock Vadose Zone

In upland environments, roots commonly extend deep below soil into partially saturated bedrock. This Bedrock Vadose Zone (BVZ) has been shown to store and circulate water, host organic carbon respiration and serve as a critical source of rock-derived nutrients. However, the extent to which deep roots influence chemical weathering rates remains poorly understood. Here, we report 4 years of depth-resolved major ion chemistry over a 16-m thick BVZ hosting a deep rhizosphere in a catchment subject to a Mediterranean climate. These data allow development and validation of a reactive transport model (RTM), revealing that the timescales of water storage and drainage in the BVZ are sufficient to facilitate substantial chemical weathering of the shale bedrock. However, observed solute concentrations are only reproduced by the RTM when we explicitly include measured rates of CO 2(g) production meters below soil driven by the deeply rooted forest. By combining direct observations and a process-based RTM we conclude that the carbon respiration promoted by deep roots significantly enhances chemical weathering rates in the BVZ, constituting 43% ± 3% of total solute flux from the base of the BVZ to the water table.

Osorio‐Leon, Ivan D. [University of Illinois Urban↗

DOE OSTI2025

Towards Full ‘Galilei General Relativity’: Gravitational Kinematics in Bargmann Spacetimes

Because of the strict separation of mass and energy in Galilei physics, a Galilei-invariant tensor formalism is most at home in a 5-dimensional extended spacetime associated with the Bargmann-Galilei (traditionally ‘Bargmann’) group, a central extension of the Galilei group that explicitly exhibits the transformation properties of kinetic energy. While not necessary for a tensor formalism fully embodying Poincaré physics, a similar central extension of the Poincaré group to the Bargmann-Poincaré group may illuminate a path towards a strong-field ‘Galilei general relativity’. Here the Bargmann metric is generalized to curved spacetime by extending the usual 1+3 (traditionally ‘3+1’) formalism of general relativity on 4-dimensional spacetime to a 1+3+1 formalism, whose spacetime kinematics is shown to be consistent with that of the usual 1+3 formalism. On Bargmann spacetime, tensor laws governing the motion of an elementary classical material particle and the dynamics of a simple fluid reference the foliation of spacetime in a manner that partially reverts the Einstein perspective (accelerated fiducial observers, and geodesic material particles and fluid elements) to a Newton-like perspective (geodesic fiducial observers, and accelerated material particles and fluid elements subject to a gravitational force).

Cardall, Christian [ORNL] (ORCID:000000020086105X)↗

NASA NTRS2007

Model Checker for Java Programs

Java Pathfinder (JPF) is a verification and testing environment for Java that integrates model checking, program analysis, and testing. JPF consists of a custom-made Java Virtual Machine (JVM) that interprets bytecode, combined with a search interface to allow the complete behavior of a Java program to be analyzed, including interleavings of concurrent programs. JPF is implemented in Java, and its architecture is highly modular to support rapid prototyping of new features. JPF is an explicit-state model checker, because it enumerates all visited states and, therefore, suffers from the state-explosion problem inherent in analyzing large programs. It is suited to analyzing programs less than 10kLOC, but has been successfully applied to finding errors in concurrent programs up to 100kLOC. When an error is found, a trace from the initial state to the error is produced to guide the debugging. JPF works at the bytecode level, meaning that all of Java can be model-checked. By default, the software checks for all runtime errors (uncaught exceptions), assertions violations (supports Java s assert), and deadlocks. JPF uses garbage collection and symmetry reductions of the heap during model checking to reduce state-explosion, as well as dynamic partial order reductions to lower the number of interleavings analyzed. JPF is capable of symbolic execution of Java programs, including symbolic execution of complex data such as linked lists and trees. JPF is extensible as it allows for the creation of listeners that can subscribe to events during searches. The creation of dedicated code to be executed in place of regular classes is supported and allows users to easily handle native calls and to improve the efficiency of the analysis.

Visser, Willem↗

NASA NTRS2012

Wavespace-Based Coherent Deconvolution

Array deconvolution is commonly used in aeroacoustic analysis to remove the influence of a microphone array's point spread function from a conventional beamforming map. Unfortunately, the majority of deconvolution algorithms assume that the acoustic sources in a measurement are incoherent, which can be problematic for some aeroacoustic phenomena with coherent, spatially-distributed characteristics. While several algorithms have been proposed to handle coherent sources, some are computationally intractable for many problems while others require restrictive assumptions about the source field. Newer generalized inverse techniques hold promise, but are still under investigation for general use. An alternate coherent deconvolution method is proposed based on a wavespace transformation of the array data. Wavespace analysis offers advantages over curved-wave array processing, such as providing an explicit shift-invariance in the convolution of the array sampling function with the acoustic wave field. However, usage of the wavespace transformation assumes the acoustic wave field is accurately approximated as a superposition of plane wave fields, regardless of true wavefront curvature. The wavespace technique leverages Fourier transforms to quickly evaluate a shift-invariant convolution. The method is derived for and applied to ideal incoherent and coherent plane wave fields to demonstrate its ability to determine magnitude and relative phase of multiple coherent sources. Multi-scale processing is explored as a means of accelerating solution convergence. A case with a spherical wave front is evaluated. Finally, a trailing edge noise experiment case is considered. Results show the method successfully deconvolves incoherent, partially-coherent, and coherent plane wave fields to a degree necessary for quantitative evaluation. Curved wave front cases warrant further investigation. A potential extension to nearfield beamforming is proposed.

Bahr, Christopher J.↗

DOE OSTI2021

Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm

The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applications. Modern phase retrieval approaches usually rely on gradient descent methods in a nonlinear minimization framework. Calculating closed-form gradients for use in these methods is tedious work, and formulating second order derivatives is even more laborious. Additionally, second order techniques often require the storage and inversion of large matrices of partial derivatives, with memory requirements that can be prohibitive for data-rich imaging modalities. We use a reverse-mode automatic differentiation (AD) framework to implement an efficient matrix-free version of the Levenberg-Marquardt (LM) algorithm, a longstanding method that finds popular use in nonlinear least-square minimization problems but which has seen little use in phase retrieval. Furthermore, we extend the basic LM algorithm so that it can be applied for more general constrained optimization problems (including phase retrieval problems) beyond just the least-square applications. Since we use AD, we only need to specify the physics-based forward model for a specific imaging application; the first and second-order derivative terms are calculated automatically through matrix-vector products, without explicitly forming the large Jacobian or Gauss-Newton matrices typically required for the LM method. We demonstrate that this algorithm can be used to solve both the unconstrained ptychographic object retrieval problem and the constrained “blind” ptychographic object and probe retrieval problems, under the popular Gaussian noise model as well as the Poisson noise model. We compare this algorithm to state-of-the-art first order ptychographic reconstruction methods to demonstrate empirically that this method outperforms best-in-class first-order methods: it provides excellent convergence guarantees with (in many cases) a superlinear rate of convergence, all with a computational cost comparable to, or lower than, the tested first-order algorithms.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Probing O 2 dependence of hydroperoxy-butyl reactions via isomer-resolved speciation

Degenerate chain-branching mechanisms of n-alkanes are centered on the formation of hydroperoxy-alkyl radicals ($\dot{Q}$OOH), formed via $\dot{R}$ + O 2 reactions, and the ensuing competition between unimolecular decomposition and second-O 2 -addition. Quantitative measurements of partially oxidized intermediates formed via reactions of $\dot{Q}$OOH provide critical constraints that are required for accurate modeling of combustion chemistry. To examine the influence of temperature and oxygen concentration on intermediates from unimolecular decomposition of $\dot{Q}$OOH, isomer-resolved speciation measurements were conducted on n-butane oxidation at 835 Torr in a jet-stirred reactor (JSR) from 500 – 900 K. Resulting from negative-temperature coefficient behavior, cyclic ether formation peaked at two temperatures, 650 K and 800 K, which were selected for separate experiments to quantify the O 2 -dependence of species profiles using O 2 concentrations of 4.2 · 10 17 – 1.1 · 10 19 molecules cm –3 . Utilizing vacuum-ultraviolet absorption spectroscopy and electron-impact mass spectrometry, cyclic ether isomers were quantified separately, including explicit resolution of cis– and trans– isomers of 2,3-dimethyloxirane. Stereoisomers of 2-butene were also quantified explicitly. For all cyclic ethers, a common trend in O 2 -dependence emerged: species concentrations reach a maximum near 3.0 · 10 18 molecules cm –3 (equivalence ratio of 0.5). Although quantitative disparities are evident, chemical kinetics modeling qualitatively reproduces the O 2 dependence of species at 650 K. However, at 800 K, weak dependence on O 2 is predicted, which is in contrast with the measurements. Two carbonyls, diacetyl and methyl vinyl ketone, were also quantified and follow similar dependence on [O 2 ] and temperature as the cyclic ethers, which indicates some fraction forms via $\dot{Q}$OOH-mediated reactions. The discrepancies between the measured and model-predicted species profiles indicate that sub-mechanisms for important intermediates may require additional elementary reactions, including stereochemical-specific reactions, to improve the fidelity of n-alkane combustion modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Platform for Remote Deployment and Training for Enhanced Building Operation Practices (Building Re-Tuning and On-going Commissioning)

While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

The Role of Atmospheric Rivers on Groundwater: Lessons Learned From an Extreme Wet Year

Abstract In the coastal regions of the western United States, atmospheric rivers (ARs) are associated with the largest precipitation generating storms and contribute up to half of annual precipitation, but the impact of ARs on the integrated hydrologic cycle, specifically on groundwater storage and hydrodynamics, is largely unknown. To better explore the hydrologic behavior of AR versus non‐AR event precipitation, we present a novel combination of two water tracking methods (one in the atmosphere and one in the subsurface) to explicitly track the full lifecycle of water parcels generated by ARs. Simulations of northern California's Cosumnes River watershed during the record wet 2017 water year are performed via the coupling of a high‐resolution regional climate model and a land surface‐groundwater model accounting for lateral groundwater flow. Despite ARs contributing more precipitation than non‐AR storms, we find less AR water is preferentially stored in aquifers by year end. Fractionally, ARs result in 300% less snow derived groundwater‐recharged compared to non‐AR precipitation. Rain‐on‐snow (RoS) plays an important role in AR‐driven discharge, where over 50% of total discharge from ARs snow is from RoS events. Finally, despite record‐breaking annual precipitation, simulated groundwater depletion occurs by year end due to estimates of groundwater pumping activities. The results from these simulations serve as a partial analogue of future hydrologic conditions where ARs are expected to intensify and provide a greater fraction of annual precipitation due to climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Diazotrophs Show Signs of Restoration in Amazon Rain Forest Soils with Ecosystem Rehabilitation

Biological nitrogen fixation can be an important source of nitrogen in tropical forests that serve as a major CO 2 sink. Extensive deforestation of the Amazon is known to influence microbial communities and the biogeochemical cycles they mediate. However, it is unknown how diazotrophs (nitrogen-fixing microorganisms) respond to deforestation and subsequent ecosystem conversion to agriculture, as well as whether they can recover in secondary forests that are established after agriculture is abandoned. To address these knowledge gaps, here we combined a spatially explicit sampling approach with high-throughput sequencing of nifH genes. The main objectives were to assess the functional distance decay relationship of the diazotrophic bacterial community in a tropical forest ecosystem and to quantify the roles of various factors that drive the observed changes in the diazotrophic community structure. We observed an increase in local diazotrophic diversity (α-diversity) with a decrease in community turnover (β-diversity), associated with a shift in diazotrophic community structure as a result of the forest-to-pasture conversion. Both diazotrophic community turnover and structure showed signs of recovery in secondary forests. Changes in the diazotrophic community were primarily driven by the change in land use rather than differences in geochemical characteristics or geographic distances. The diazotroph communities in secondary forests resembled those in primary forests, suggesting that at least partial recovery of diazotrophs is possible following agricultural abandonment. IMPORTANCE The Amazon region is a major tropical forest region that is being deforested at an alarming rate to create space for cattle ranching and agriculture. Diazotrophs (nitrogen-fixing microorganisms) play an important role in supplying soil N for plant growth in tropical forests. It is unknown how diazotrophs respond to deforestation and whether they can recover in secondary forests that establish after agriculture is abandoned. Using high-throughput sequencing of nifH genes, we characterized the response of diazotrophs’ β-diversity and identified major drivers of changes in diazotrophs from forest-to-pasture and pasture-to-secondary-forest conversions. Studying the impact of land use change on diazotrophs is important for a better understanding of the impact of deforestation on tropical forest ecosystem functioning, and our results on the potential recovery of diazotrophs in secondary forests imply the possible restoration of ecosystem functions in secondary forests.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A mechanistic interpretation of Nelson curves for PVP failures under high temperature hydrogen attack

As an empirically established design criterion, Nelson curves that relate the service temperature and the allowable hydrogen partial pressure have been developed and utilized for more than sixty years in pressure vessels and piping (PVP) safety design. Despite a relatively clear thermodynamic understanding of the high-temperature-hydrogen-attack (HTHA) problem, the detailed fracture process on the microstructural length scales, however, remains elusive, and a quantitative assessment of the PVP lifetime under HTHA from the available creep fracture dataset is still not possible. This work develops a microstructure-informed and micromechanics-based model by incorporating a synergy between hydrogen transport and intergranular-cavity-based fracture process. Based on the available creep lifetime data of C-0.5Mo steels, we are able to calibrate material constitutive parameters, and then conduct nonlinear finite element simulations that reveal a real-time stress-induced hydrogen diffusional transport along grain boundaries, coupled with a microstructure-explicit failure process, from which Nelson curves can be computed. Such failure analyses allow us to delineate two distinct regimes on the Nelson curves, i.e., dislocation-creep-controlled or grain boundary diffusion-assisted cavity growth. More importantly, we found that a small change of the pipe thickness and applied stresses can significantly shift these lifetime curves. However, these two parameters are usually not provided in Nelson curves, thus limiting their usage in material selection and safety design. In conclusion, this discrepancy can clearly be mitigated by extensive parametric studies from our micromechanical modeling/simulation framework.

36 MATERIALS SCIENCE↗

NASA NTRS1989

An investigation of using an RQP based method to calculate parameter sensitivity derivatives

Estimation of the sensitivity of problem functions with respect to problem variables forms the basis for many of our modern day algorithms for engineering optimization. The most common application of problem sensitivities has been in the calculation of objective function and constraint partial derivatives for determining search directions and optimality conditions. A second form of sensitivity analysis, parameter sensitivity, has also become an important topic in recent years. By parameter sensitivity, researchers refer to the estimation of changes in the modeling functions and current design point due to small changes in the fixed parameters of the formulation. Methods for calculating these derivatives have been proposed by several authors (Armacost and Fiacco 1974, Sobieski et al 1981, Schmit and Chang 1984, and Vanderplaats and Yoshida 1985). Two drawbacks to estimating parameter sensitivities by current methods have been: (1) the need for second order information about the Lagrangian at the current point, and (2) the estimates assume no change in the active set of constraints. The first of these two problems is addressed here and a new algorithm is proposed that does not require explicit calculation of second order information.

Beltracchi, Todd J.↗