Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Comparative framework”

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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electrochemical carbon dioxide capture to close the carbon cycle

Electrochemical CO 2 capture technologies are gaining attention due to their flexibility, their ability to address decentralized emissions (e.g., ocean and atmosphere) and their fit in an electrified industry. In the present work, recent progress made in electrochemical CO 2 capture is reviewed. The majority of these methods rely on the concept of “pH-swing” and the effect it has on the CO 2 hydration/dehydration equilibrium. Through a pH-swing, CO 2 can be captured and recovered by shifting the pH of a working fluid between acidic and basic pH. Such swing can be applied electrochemically through electrolysis, bipolar membrane electrodialysis, reversible redox reactions and capacitive deionization. In this review, we summarize main parameters governing these electrochemical pH-swing processes and put the concept in the framework of available worldwide capture technologies. We analyse the energy efficiency and consumption of such systems, and provide recommendations for further improvements. Although electrochemical CO 2 capture technologies are rather costly compared to the amine based capture, they can be particularly interesting if more affordable renewable electricity and materials (e.g., electrode and membranes) become widely available. Furthermore, electrochemical methods have the ability to (directly) convert the captured CO 2 to value added chemicals and fuels, and hence prepare for a fully electrified circular carbon economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Kinetic origins of the metastable zone width in the manganese oxide Pourbaix diagram

Pourbaix diagrams show solid–aqueous phase stability as a function of pH and redox potential and can be a valuable tool to guide the hydrothermal synthesis of transition metal oxides. However, the Pourbaix diagram is based on thermodynamics, and nucleation kinetics are not readily apparent in this framework. Here, we conduct a combined experimental and theoretical study to measure the onset of MnO 2 precipitation from an MnO 4 - (aq) solution at various pH conditions, which we then compare against Pourbaix diagram phase boundaries. Using a combination of in situ X-ray absorption spectroscopy and X-ray wide-angle scattering, we directly observe the transformation kinetics from the tetrahedral MnO 4 - (aq) ion to octahedrally coordinated Mn pre-nuclei, as well as its initiation into crystalline δ'-MnO 2 at various pH. The kinetics of octahedral-Mn precursor availability is observed to govern induction times of crystalline MnO 2 nucleation, which results in a metastable zone width in the Mn–H 2 O Pourbaix diagram. These results suggest that synthesis conditions often need to be prepared far beyond the phase boundaries in a Pourbaix diagram to initiate crystallization within a reasonable timescale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Analytical gradients for molecular-orbital-based machine learning

We report molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. Here, we present the derivation, implementation, and numerical demonstration of MOB-ML analytical nuclear gradients, which are formulated in a general Lagrangian framework to enforce orthogonality, localization, and Brillouin constraints on the molecular orbitals. The MOB-ML gradient framework is general with respect to the regression technique (e.g., Gaussian process regression or neural networks) and the MOB feature design. We show that MOB-ML gradients are highly accurate compared to other ML methods on the ISO17 dataset while only being trained on energies for hundreds of molecules compared to energies and gradients for hundreds of thousands of molecules for the other ML methods. The MOB-ML gradients are also shown to yield accurate optimized structures at a computational cost for the gradient evaluation that is comparable to a density-corrected density functional theory calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Comparison between Alcator C-Mod ICRF experiments and 3D full wave simulations

Reliable modeling of ion cyclotron range of frequencies (ICRF) antenna performance is essential for interpreting present experiments and guiding the design of future reactors. In this work, a 3D model of the Alcator C-Mod field-aligned antenna is implemented in the Petra-M finite-element framework [S. Shiraiwa et al 2023 Nucl. Fusion 63 026024] and benchmarked against experimental results. Four experimental cases are examined. First, the simulated rectified sheath potentials on the antenna limiters are compared with measurements from a power tapering experiment. Second, proof-of-principle far-field sheath simulations are performed. In scenarios with low single-pass absorption, simulations predict enhanced sheath potentials on a distant poloidal limiter in the far field of the antenna, consistent with experimental observations. Third, the simulated antenna loading during edge localized modes follows experimental trends and appears to be dominated by the density gradient at the pedestal. Finally, Petra-M predicts the unintended excitation of high-$k$ ∥ modes during monopole phasing operation, in agreement with experimental evidence of poor wave coupling and accessibility to the plasma core. Overall, reasonable agreement is found between the simulations and experiments. At the same time, areas of imperfect agreement are identified. These provide important guidance on the limits of the current state-of-the-art modeling, which should be kept in mind when using it as a predictive tool for future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The PDF perspective on the tracer-matter connection: Lagrangian bias and non-Poissonian shot noise

ABSTRACT We study the connection of matter density and its tracers from the probability density function (PDF) perspective. One aspect of this connection is the conditional expectation value 〈δtracer|δm〉 when averaging both tracer and matter density over some scale. We present a new way to incorporate a Lagrangian bias expansion of this expectation value into standard frameworks for modelling the PDF of density fluctuations and counts-in-cells statistics. Using N-body simulations and mock galaxy catalogues we confirm the accuracy of this expansion and compare it to the more commonly used Eulerian parametrization. For haloes hosting typical luminous red galaxies, the Lagrangian model provides a significantly better description of 〈δtracer|δm〉 at second order in perturbations. A second aspect of the matter-tracer connection is shot-noise, i.e. the scatter of tracer density around 〈δtracer|δm〉. It is well known that this noise can be significantly non-Poissonian and we validate the performance of a more general, two-parameter shot-noise model for different tracers and simulations. Both parts of our analysis are meant to pave the way for forthcoming applications to survey data.

Friedrich, Oliver↗
DOE OSTI2020

Magnetoresistance effects in a spin-fermion model for multilayers

Here, we consider a spin-fermion model consisting of free electrons coupled to classical spins where the latter are embedded in a quasi-one-dimensional superlattice structure consisting of spin blocks separated by spinless buffers. Using a spiral ansatz for the spins, we study the effect of the electron mediated Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction on the $\textit{T}$ = 0 ground state of the system. We find that the RKKY interaction can lead to ferromagnetic, antiferromagnetic, or intermediate spiral phases for different system parameters. When the width is much larger than the length of the individual blocks, the spiral phases are suppressed, and the ground state oscillates between ferromagnetic and antiferromagnetic orders as the size of the buffer regions is varied. This is accompanied by a corresponding oscillation in the Drude weight reflecting an increased conductivity in the ferromagnetic state compared to the antiferromagnetic one. These results are reminiscent of classic giant magnetoresistance phenomena observed in a similar geometry of thin sandwiched magnetic and nonmagnetic layers. Our analysis provides a robust framework for understanding the role of the RKKY interaction on the ground-state order and corresponding transport properties of such systems, extending beyond the conventional perturbative regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Assessing Electrolyte Fluorination Impact on Calendar Aging of Blended Silicon-Graphite Lithium-Ion Cells Using Potentiostatic Holds

Silicon-based lithium-ion batteries have started to meet cycle life metrics, but they exhibit poor calendar life. Here, electrolyte fluorination impact on calendar fade of blended silicon-graphite anodes is explored using a LiPF 6 in EC:EMC:FEC electrolyte vs LiBOB in EC:EMC electrolyte. We utilize a combined experimental-modeling approach applying potentiostatic voltage holds (V-hold) to evaluate electrolyte suitability for calendar life in a shortened testing timeframe (~2 months). Our theoretical framework deconvolutes the irreversible parasitic capacity losses (lithium lost to the solid electrolyte interphase) from the V-hold electrochemical data. Unfluorinated electrolyte (dominant LiBOB reduction) exhibits higher cell resistance as compared to fluorinated electrolyte (dominant FEC reduction). Both systems have similar irreversible capacities during the voltage hold duration with slower rate of parasitic capacity loss for the LiBOB system. Extrapolation of the parasitic losses to end of life capacity fade of 20% shows LiBOB electrolyte outperforming LiPF 6 electrolyte in calendar life. The results demonstrate the applicability of the V-hold protocol as a rapid material screening tool providing semi-quantitative calendar lifetime estimates.

25 ENERGY STORAGE↗
DOE OSTI2021

Extracting Material Property Measurement Data from Scientific Articles

Machine learning-based prediction of material properties is often hampered by the lack of sufficiently large training datasets. The majority of such measurement data is embedded in scientific literature and the ability to automatically extract these data is essential to support the development of reliable property prediction methods. In this work, we describe a methodology for an automatic property extraction framework using material solubility as the target property. We create an annotated dataset containing tags for solubility-related entities using a combination of regular expressions and manual tagging. We then compare five entity recognition models leveraging both token-level and span-level architectures on the task of classifying solute names, solubility values, and solubility units. Additionally, we explore a novel pretraining approach that leverages automated chemical name and quantity extraction tools to generate large datasets that do not rely on intensive manual effort. Finally, we perform an analysis to identify the causes of classification errors.

Panapitiya, Gihan U.↗
DOE OSTI2022

Magnetic-Field Diffusion Effects in Beam Position Monitors II: Application to Calibration Single-Pulse Data

Beam position monitors (BPMs) provide time-resolved measurements of the current and centroid position of high-current electron beams in linear induction accelerators (LIAs). One of the types of detectors used in BPMs is the B-dot loop, which generates a signal from the EMF due to the time varying magnetic flux through the loop. If some of the boundaries of the loop are composed of thick metal walls with finite conductivity, the resulting signal must be corrected for the magnetic field diffusion into the metal. From first principles, we have derived the perturbation to BPM measurements due to this effect. The theoretical framework was used to design an algorithm for signal correction that does not require knowledge of the time history of the magnetic flux being measured. Corrected signals based on that process compared favorably with the know reference signals in a laboratory calibration test sequence.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Preliminary Feasibility of Printing, Microstructure Analysis and Mechanical Performance of a Down Selected Ni Alloy

This report is submitted as completion of a Milestone 3 deliverable under work package ORNL CT-23OR1304051 in support of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is aiming at the faster incorporation of new materials and manufacturing technologies into complex nuclear-related systems. An integrated approach, combining advanced characterization, high-throughput and accelerated testing, modeling and simulation including machine learning and artificial intelligence will be employed. While 316H (Fe-16-18Cr-10-14Ni-2-3Mo-0.04-0.1C) has been identified as a key alloy to be integrated into the AMMT accelerated alloy qualification approach due its relevance for many current and future nuclear energy reactors, many other alloys could be considered for the advanced fabrication of innovate high-performance nuclear components. ANL, INL, ORNL and PNNL are collaborating on identifying the most promising alloy candidates relevant for the AMMT program. A selection criteria matrix was established to evaluate the alloys considering their relative importance and technological readiness levels for nuclear energy applications, with a focus on laser powder bed fusion (LPBF). Due to the broad range of potential candidate alloys, ORNL and INL focused on Ni-based alloys, while ANL and PNNL mainly evaluated Fe-based alloys. PNNL previously published materials scorecards reports on several key alloys and this report is providing a broader overview of Ni-based candidate alloys, expending beyond alloys well-known to the nuclear community. Of particular interest are alloys that are currently commercially available in powder form due to the growing demand from other industries that have invested heavily in additive manufacturing. Among these alloys, Haynes 282 (Fe-20Cr-20Co-8Mo) was selected due to its superior strength at high temperature compared to the code-qualified alloy 617 (Ni-20-24Cr-10-15Co-8-10Mo). To assess the integration of this new alloy into the AMMT digital manufacturing framework, we performed the rapid optimization of alloy 282 printing parameters on a Renishaw 250 machine, the fabrication of sufficient materials for extensive characterization and mechanical testing both at ORNL and INL, and added the printing data into the digital platform via the Peregrine software. A detailed analysis of the LPBF 718 alloy was also conducted, with creep specimens being tested at 600-650°C and characterized by advanced electron microscopy. The alloy superior mechanical strength and great printability associated with the extensive database that has already been generated highlight the promising potential of LPBF 718 as a candidate alloy for the AMMT program. INL, ANL and PNNL have generated similar reports and all the information will be compiled into a final M2 milestone report to provide the AMMT leadership team with clear recommendations on the down selection of reactor materials, as well as establish a roadmap for the qualification of these selected alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Importance of Multiplicity Fluctuations in Entropy Scaling

One of the greatest uncertainties in heavy-ion collisions is the description of the initial state. Different models predict a wide range of initial energy density distributions based on their underlying assumptions. Final flow harmonics are sensitive to these differences in the initial state due to the nearly linear mapping between eccentricities and anisotropic flow harmonics. The Trento code uses a model-agnostic approach by phenomenologically parameterizing the initial state and constraining those parameters from a Bayesian analysis. There the multiplicity fluctuations were determined by a one parameter Γ distribution. However, initial-state models arising from the Color-Glass Condensate (CGC) framework lead to an initial energy density which is outside the functional form considered in Trento and its later Bayesian analyses because they rely on log-normal multiplicity fluctuations. We compare T A T B scaling (CGC-like) to √T A T B scaling (preferred from a Trento Bayesian analysis) and find that the T A T B form together with log-normal fluctuations is a reasonable candidate to describe the multiplicity fluctuations but leads to larger eccentricities, which would affect the extraction of viscosity in small systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

A Nonparametric Method for the Inference of Halo Occupation Distributions

The galaxy–halo connection traces processes by which galaxies form and evolve. The halo occupation distribution (HOD) describes the relationship between galaxies and their host dark matter haloes. Measurements of the galaxy two-point correlation function (2PCF) allow us to extract information about the HODs of observed galaxy samples. Several parametric HOD models have been proposed in the literature, but the choice of parameterization restricts the space of possible HODs. To resolve this issue, we introduce a nonparametric HOD fitting method in which we train an emulator to learn the mappings among the galaxy 2PCF, physical properties used to select galaxy samples, and the HOD, all obtained from simulated past light cones constructed with the Santa Cruz semianalytic model. Implementing this emulator within a likelihood analysis framework, we derive constraints on the HOD of a galaxy sample when provided with a measurement of its 2PCF. Using the emulator to accelerate likelihood evaluations, we test the nonparametric HOD approach on a set of 2PCFs for mock galaxy samples drawn from the TNG100-1 simulation and selected above threshold values of stellar mass and star formation rate. Our framework is able to recover TNG100-1 HODs within 0.2 dex. We use the TNG100-1 mocks to tune the reported uncertainties to estimate those expected in the analysis of observations. Comparing to parametric HOD modelling routines applied to the same mock galaxy samples, our approach consistently infers the HOD with comparable or greater precision and accuracy.

Kennedy, Jacob [Rutgers Univ., Piscataway, NJ (Uni↗
DOE OSTI2026

Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study

National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1980

Standing Alfven wave current system at Io: Voyager 1 observations

The enigmatic control of the occurrence frequency of Jupiter's decametric emissions by the satellite Io is explained theoretically on the basis of its strong electrodynamic interaction with the corotating Jovian magnetosphere leading to field aligned currents connecting Io with the Jovian ionosphere. Direct measurements of the perturbation magnetic fields due to this current system were obtained by the magnetic field experiment on Voyager 1 on 5 March 1979 when it passed within 20,500 km south of Io. An interpretation in the framework of Alfven waves radiated by Io leads to current estimates of 2.8 million amps. A mass density of 7400 to 13600 proton mass units per Cu cm is derived which compares very favorably with independent observations of the torus composition characterized by 7-9 proton mass units per electron for a local electron density of 1050 to 1500 per cu cm. The power dissipated in the current system may be important for heating the Io heavy ion torus, inner magnetosphere, Jovian ionosphere, and possibly the ionosphere or even the interior of Io.

Acuna, M. H.↗
NASA NTRS1988

A comparison of single-cycle versus multi-cycle proof testing strategies

Proof testing was a useful supplement to conventional nondestructive evaluation (NDE) of space shuttle main engine (SSME) components. Since many of these components involve thin sections and high toughness materials, such as Inconel 718, conventional single-cycle proof test logic is not applicable due to the propensity for stable crack growth during the proof tests. Experience with five-cycle proof testing of SSME components is summarized and a framework is outlined for understanding multi-cycle proof testing using the fracture mechanics concept of a resistance curve. Extreme value statistics are also used to propose an empirical approach to compare the advantages and disadvantages of single- versus multi-cycle proof testing. The importance of the initial flaw size distribution and specimen thickness in such a comparison is also discussed.

Hudak, Stephen J., Jr.↗
NASA NTRS2018

Multidisciplinary Design Optimization and Cruise Mach Number Study of Truss-Braced Wing Aircraft

The Subsonic Ultra Green Aircraft Research (SUGAR) Phase III was led by Dr. Rakesh K. Kapania and Dr. Joseph A. Schetz at the Multidisciplinary Analysis and Design Center for Advanced Vehicles, Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg VA. The research was performed from December 2014 to December 2015. Three major areas were investigated: Multidisciplinary Design Optimization (MDO) studies of truss braced wing (TBW) and strut braced wing (SBW) vehicles at cruise Mach numbers of 0.7 and 0.8 for a flight mission similar to current market single aisle configurations. The performance and the characteristics of the optimized vehicles were compared to the SUGAR Phase II TBW vehicle. These results were obtained without applying any of the extended transonic aerodynamic and aeroelastic tools that will be discussed later. It was found that the cruise Mach number has a large effect on the best “truss” configuration. At Mach 0.7, an SBW has a better fuel consumption and better take-off gross weight (TOGW). However, at Mach 0.8, the TBW is superior because the jury strut aids in satisfying the flutter constraint; Two-dimensional, steady, transonic aerodynamic analysis of the Boeing Airfoil J (BACJ) airfoil was performed for a range of thickness ratios, Mach numbers and lift coefficients. Reynolds-averaged Navier-Stokes (RANS) equations were solved to obtain the lift-curve slope, wave drag coefficient, the location of the center of pressure and to predict the separation at the trailing edge, which may lead to buffeting. One of the goals was to develop a database of lift-curve slope and the location of center of pressure, which could be used in a transonic aeroelastic analysis. Another goal was to compare the wave drag coefficients to those predicted by Lock’s fourth-power law and also to compare the transonic effects obtained from RANS simulations to those predicted by the Korn equations. A third goal was to develop a buffet boundary, which can be integrated into the MDO framework to prevent the optimized designs from probable buffeting; A state-space transonic aeroelastic analysis tool was developed, which can incorporate the nonlinear transonic effects in the unsteady aerodynamics but is yet computationally cheap when used within the VT MDO framework. The aeroelastic analysis uses Leishman- Beddoes (LB) indicial functions, which generated a state-space representation of the aeroelastic system. The indicial functions allow the incorporation of data for steady lift-curve slope and location of the center of pressure. Thus, the steady transonic effects are included, and the unsteady aerodynamic responses are a linearization about the steady results. The aeroelastic approach discretizes the wing into numerous strips, which results in a large eigenvalue problem as each strip has eight augmented aerodynamic states as per the LB theory. Thus, to reduce the computation expense, a reduced order model (ROM) was developed. The approach was validated using a few examples.

Kapania, Rakesh K.↗
NASA NTRS2021

Improved representation of the global dust cycle using observational constraints on dust properties and abundance

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of 2 relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with a geometric diameter up to 20 µm (PM20) is approximately 5000 Tg yr−1, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this dataset is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

Dust cycle↗
NASA NTRS2021

Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.

Jawairia Ahmad↗