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At least 973 records · Page 54

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗

Multi-scale model based design of membrane reactor/separator processes for intensified hydrogen production through the water gas shift reaction

This paper aims to first quantify the impact of various diffusion models (Maxwell-Stefan, Wilke, Dusty-Gas) on the predictions of a multi-scale membrane reactor/separator mathematical model, and to then demonstrate this model's use for the design and process intensification of membrane reactor/separator systems for hydrogen production. This multi-scale model captures velocity, temperature and species' concentration profiles along the catalyst pellet's radial direction, and along the reactor's axial direction, by solving the momentum, energy, and species transport equations, accounting for convection, conduction, reaction, and diffusion mechanisms. In the first part of work, the effect of pellet-scale design parameters (mean pore diameter, volumetric porosity, tortuosity factor, etc.) and various species' flux models on the model predictions is studied. In the second part, the study focuses on the comparison, in terms of their process intensification characteristics, of various hydrogen production processes. These include a conventional high-temperature shift reactor (HTSR)/low-temperature shift reactor (LTSR) sequence, a novel HTSR/membrane separator (MS)/LTSR/MS sequence, and a process that involves low-temperature shift membrane reactors-LTSMR in a series.

08 HYDROGEN↗

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗

Multi-material swept face remapping on polyhedral meshes

Remapping is a conservative interpolation of a discretized intensive quantity between two meshes. In this article, we propose a novel multi-material flux remapping method that avoids the geometric computation of mesh-mesh intersections needed for an accurate intersection based remap. The flux remap is applicable to scalar quantities such as material density describing the multi-material flow between meshes with the same connectivity but small mesh displacements. Herein, the method is described for two- and three-dimensional polygonal/polyhedral meshes as it is implemented in Portage. Another open source library, Tangram, is used to calculate material interfaces in cells containing more than one material. Performance and accuracy of the flux remap are discussed with respect to Arbitrary Lagrangian-Eulerian simulations and compared to an accurate intersection based remap. In particular, cyclic remapping shows that the accuracy of the flux remap is limited to first order on material boundaries while maintaining second order accuracy in pure material regions.

97 MATHEMATICS AND COMPUTING↗

Multi-material ALE remap with interface sharpening using high-order matrix-free finite element methods

The arbitrary Lagrangian-Eulerian (ALE) technique involves remapping field quantities from a Lagrangian mesh to an optimized mesh in a conservative, accurate and bounds-preserving manner. For methods based on arbitrary order finite elements, as described in a reference, material volume fractions are advected in pseudo-time using flux-corrected transport (FCT) without any form of interface reconstruction. In practice, this can lead to excessive propagation of small volume fractions throughout the domain. In addition, this method requires assembly of a global advection matrix to compute the bounds-preserving low-order FCT solution. In this work, we introduce a new approach for ALE remap using a high-order matrix-free technique which incorporates a flux modification to sharpen material interfaces in a conservative manner. Our approach begins with computing a bounds-preserving low-order solution to the ALE remap equations at the element level. We then compute a sharp interface solution (not guaranteed to be bounds-preserving) which comes from solving an augmented version of the ALE remap equations with a conservative flux modification which acts to sharpen material volume fractions based on their gradients and transport directions. Using the sharp interface solution, we make global corrections to the bounds-preserving solution while maintaining preservation of bounds. By blending with the sharpened solution at the global level we are able to globally conserve mass without hindering the remap pseudo-time step. This new interface-aware ALE remap method is based entirely on partial assembly techniques where globally assembled matrix operators are no longer needed, resulting in a globally matrix-free FCT method for multi-material, multi-field ALE remap with high performance on GPU architectures. We present results of our new remap method on 1D, 2D and 3D benchmarks and describe the algorithmic tailoring for GPU architectures that was developed.

Vargas, Arturo [Lawrence Livermore National Labora↗

Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding

The paper considers testing and signal identification for covariance matrices from two populations of marginally sub-Gaussian distributed. A multi-level thresholding procedure is proposed for testing the equality of two high-dimensional covariance matrices, which is designed to detect sparse and faint differences between the covariances. A novel -statistic composition is developed to establish the asymptotic distribution of the thresholding statistics in conjunction with the matrix blocking and the coupling techniques. It is shown that the proposed test is more powerful than the existing tests in detecting sparse and weak signals in covariances. Multiple testing procedures are constructed to discover different covariances and the sub-groups of variables with different covariance structures between the two populations. The proposed procedures are based on the multi-level thresholding test, which are able to control the false discovery proportion () with high power. Simulation experiments and a case study on the returns of the S&P 500 stocks before and after the COVID-19 pandemic are conducted to demonstrate and compare the utilities of the proposed methods.

97 MATHEMATICS AND COMPUTING↗

Multi-material additive manufacturing of aluminum 6061-T6 alloy with stainless steel 304: Suppression of intermetallic compounds and interface growth mechanism

Fabricating integrated aluminum-steel structures is difficult because of metallurgical incompatibilities that promote intermetallic compound (IMC) formation at their interfaces. This work introduces a practical route for additively manufacturing 6061-T6 aluminum alloy (AA6061-T6) directly onto 304 stainless steel (SS304) using a high shear strain rate-assisted interfacial bonding mechanism. Through the friction extrusion deposition-based additive manufacturing method, both single- and multi-layer deposits of AA6061-T6 were successfully fabricated on SS304, yielding a robust hybrid multi-material structure. Comprehensive analyses of deposition quality, interface porosity, and bonding performance showed that the interface achieved a tensile strength exceeding 154 MPa under quasi-static loading. Microstructural observations revealed that the deposited aluminum layers experienced severe plastic deformation, resulting in pronounced grain refinement. Importantly, the interfacial zone was found to be free of brittle IMCs, instead containing a thin amorphous layer that evolved through a non-linear reaction-zone growth law. This solid-state additive strategy establishes a promising pathway for lightweight structural systems, nuclear energy component cladding, and multifunctional engineering components, redefining how dissimilar metals can be integrated for advanced applications.

Aluminum alloy↗

Fractionation of critical metals from authentic acid mine drainage using a multi-bed immobilized amine sorbent setup: A field site study

Here for the first time reported, a flow-through multi-fixed bed immobilized amine/silica sorbent strategy was employed to fractionate purified critical metals from authentic acid mine drainage (AMD). The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory’s (NETL) patent-pending Multi-functional Sorbent Technology (MUST) sorbents were used to recover critical metals from AMD at the Pittsburgh Botanic Garden (Pittsburgh, PA USA). By adjusting the AMD/sorbent ratio, we recovered > 80% of pure adsorbed Mn (by adsorbed metal weight) and >90% pure adsorbed Al at lab-scale. Further optimizing the weight hourly space velocity (WHSV) enhanced the rate of adsorbed Al recovery by over five times, justifying a field site test. After treating >100 L of AMD at the field site, the optimized polyamine/epoxysilane/aminosilane sorbent recovered approximately 0.7 wt% adsorbed Al at > 90% purity. A tangible amount of purified aluminum hydroxide [Al(OH) 3 ] and aluminum sulfate [Al 2 (SO 4 ) 3 ] solids were then recovered after eluting and precipitating the previously adsorbed metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modular multi-interface nanocrystals for enhanced ethanol oxidation electrocatalysis

Electrochemical processes that utilize biomass-derived ethanol as a source of electrons and protons offer a sustainable energy strategy, yet their practical implementation is limited by sluggish ethanol oxidation reaction (EOR) kinetics and catalyst poisoning. Here, in this study, we report a modular multi-interface nanocrystal catalyst comprising core/shell Co 2 P/Pd and Pd-Au heterostructured interfaces that exhibit complementary functions for the enhanced EOR catalysis. The Co 2 P/Pd interface boosts Pd atom utilization and lowers the kinetic barriers for ethanol-to-acetate conversion, while the Pd-Au interface effectively alleviates CO poisoning caused by C–C bond cleavage of ethanol. In-depth analyses using in situ attenuated total reflectance-surface-enhanced infrared absorption spectroscopy, differential electrochemical mass spectrometry, and density functional theory calculations elucidate the mechanistic roles of these interfaces. The optimized Co 2 P/Pd-Au 0.08 nanorods achieve an excellent mass activity, underscoring the potential of modular, multi-interface nanocrystals for advancing EOR catalysis and offering a generalizable strategy for broader catalytic innovations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A systematic analytical framework for multi-source municipal solid waste characterization for energy recovery

Advancing municipal solid waste (MSW) management from disposal-oriented practices toward circular, value-driven systems requires standardized methodologies capable of identifying material composition and resource recoverable potential at the point of generation. Despite extensive research, MSW characterization remains fragmented due to inconsistences in sampling methodologies, waste sorting categories, and temporal coverage across previous studies which limit cross-site comparability, reproducibility, and constrain the reliable evaluation of potential resource recovery pathways. This lack of consistency has hindered the development of a unified framework for MSW characterization and resource assessment. This study introduces a standardized, field-validated protocol for MSW sampling and composition analysis that ensures consistent, traceable data across diverse waste sources. The protocol integrates randomized spatial sampling, systematic material sorting, and controlled subsampling for multi-site and multi-season field campaigns. Validation included MSW collection from residential, grocery, restaurant, and school MSW streams across five U.S. states, including Maryland, Idaho, Virginia, Ohio, and Mississippi, to demonstrate the protocol’s ability to identify source-based composition patterns relevant to resource recovery applications. Grocery and restaurant streams were dominated by food waste and high-moisture organics, while school waste contained higher paper content and residential waste showed greater heterogeneity. Aggregation into energy-relevant fractions highlighted practical recovery pathways via anaerobic digestion or gasification, supporting data-driven planning, policy, and circular economy strategies for sustainable waste management across waste sources.

09 BIOMASS FUELS↗

Assessing high fidelity multi-component models to facilitate safeguards at Gas Centrifuge Enrichment Plants

We report that the International Atomic Energy Agency (IAEA) inspectors routinely carry out environmental sampling (ES) as a verification method. Collection of environmental swipe samples at various locations in Gas Centrifuge Enrichment Facilities (GCEPs) is an important process in detecting misuse of a declared facility and possibly the existence of undeclared nuclear material. These samples are measured for isotopic composition in uranium containing particles by Thermal Ionization Mass Spectrometry (TIMS) or Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Even though ES is highly effective in detecting the absolute value of enrichments and their deviations from the declared values, it cannot explain the cause of those changes. Several potential explanations can serve as possibilities for particles detected above or other than the declared enrichment. These include normal and non-malicious events such as the design of the enrichment cascades, unintentional failures of the machines, or overshoot during startup of a cascade. It can also be the result of deliberate misuse by the facility operators. The primary objective of this work is to understand how these factors affect the enrichments produced by a cascade and quantify anticipated multi-isotopic concentrations for each case. The following methodology is employed to determine signatures at a particular facility. 1) Utilize a new two-dimensional multi-component diffusion code to obtain centrifuge performance data and use that information to design and perform cascade analysis. Compare and contrast the results with previous 1-D radially averaged solutions from the Pancake code. 2) Design a GCEP cascade with the production goal of 19.75% 235 U for each set of machine data above. Investigate two cascade scenarios that include enrichment of natural uranium (NU) feed to 19.75% 235U in a single cascade compared to a two-step process of NU to 5% and then 5% to 19.75%. 3) Simulate the intentional vs. unintentional off-normal scenarios in the cascades to assess the differences in isotopic concentrations. A non-ideal squared-off cascade model developed at the University of Virginia is used to calculate flow rates and isotopic concentrations of the process gas. The analysis is performed using the Rome machine model operated at 600 m/s rotor speed. The upper and lower bounds of normal and abnormal enrichments in a typical facility are used in conjunction with ES results to understand the root causes of such observations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Multi-cycle reload analysis of a long cycle gas-cooled fast modular reactor

There is currently significant interest in deploying HALEU-fueled fast reactors, including the General Atomics (GA) Fast Modular Reactor (FMR). Such reactors can achieve very long fuel cycles, but with multi-batch loading will take decades to reach equilibrium. This motivates design and analysis of both the initial core and multi-cycle reload, which is typically performed using fast-running, deterministic fast reactor codes such as the Argonne Reactor Computation (ARC) codes. In this paper, multicycle reload of the GA FMR is analyzed using the ARC codes. The GA FMR utilizes 19.75 % enriched fuel in a 16 year cycle with a three-batch strategy, with twice-burned fuel placed on the core periphery. The GA FMR has a softened neutron spectrum due to reflecting elements in the core, so the neutronic solution is first benchmarked against the OpenMC Monte Carlo code. Discrepancy on k eff is 400–600 pcm, likely due to the softened neutron spectrum, heterogeneous fuel assembly design and central reflector. However, the rms discrepancy on the assembly power distribution is only 0.6 %, despite the presence of the central reflector. A reload strategy is devised for the first three cycles of such a reactor, ultimately spanning the first 45–48 years of its operation. The fresh core uses 19.75 %, 19.25 % and 16.75 % enriched fuel in place of fresh, once-burned and twice-burned and is then subsequently refueled with only 19.75 % enriched fuel. The cycle length is varied over 3 cycles of operation to balance fuel utilization and reactor availability, specifically with use of an extended 18-year Cycle 1, followed by a shortened 11-year Cycle 2. Cycle 3 is close to the target 16-year length. Finally, placing twice burned assemblies next to the GA FMR central reflector can reduce power peaking by 3 %, at the expense of slightly reducing the cycle length.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational modelling and experimental tank testing of the multi float WaveSub under regular wave forcing

A submerged wave device generates energy from the relative motion of floating bodies. In WaveSub, three floats are joined to a reactor; each connected to a spring and generator. Electricity generated damps the orbital movements of the floats. The forces are non-linear and each float interacts with the others. Tuning to the wave climate is achieved by changing the line lengths, so there is a need to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design. to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design.

16 TIDAL AND WAVE POWER↗

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-stage charging and discharging of electric vehicle fleets

Fleets of electric vehicles will likely shift electricity demand, and the effect of upstream charging emissions will come from generation sources that are dispatched in response. This study proposes a multi-stage charging and discharging problem to translate low-cost energy transactions into vehicle dispatch decisions. A day-ahead charging optimization problem minimizes electricity purchases and marginal emissions damages, with energy transactions becoming targets in an optimization-based dispatch strategy for an on-demand shared autonomous electric vehicle (SAEV) fleet. The framework was tested for Austin, Texas, using an agent-based simulator. Fleets can schedule charging to lower daily power costs (averaging 15.5% or $\$0.79$/day/SAEV) while reducing health damages from generation-related pollution (2.8% or $\$0.43$/day/SAEV). Finally, fleet managers can increase profits ($\$8$ per SAEV per day) by adopting a multi-stage charging and discharging strategy that can serve more passengers per day than price-agnostic dispatch strategies.

33 ADVANCED PROPULSION SYSTEMS↗

Multi-Dimensional Spectroscopy with Intense Entangled Beams: Entanglement-Enabled Phase Matching in a Collinear Beam Geometry

The experimental realization of quantum molecular spectroscopy with entangled photons remains challenging owing to the low signal-to-noise ratio resulting from the use of low-flux entangled photons. High-flux entangled photons via intense entangled beams can be used to improve the signal-to-noise ratio, but the presence of unentangled photons contaminates the quantum signal stemming from entangled photons. Here, we demonstrate how intense entangled beams can be used in multi-dimensional spectroscopy while retaining the advantage of photon entanglement. Our approach is broadly applicable to odd-ordered nonlinear spectroscopies, and it generates purely quantum spectroscopic signals. The proposed approach allows the recording of desired phase-matched signals even in a collinear beam geometry, which lifts the requirement of complicated beam geometry setups for phase matching in multi-dimensional spectroscopies.

Absorption spectroscopy↗

Rhodium-Catalyzed Alkenylation of Arenes with Multi-Substituted Olefins: Comparison of Selectivity and Reaction Rate as a Function of Olefin Identity

Rhodium-catalyzed arene alkenylation using Cu(II) carboxylates as the in situ oxidant and mono-substituted olefins has been previously reported (e.g., J. Am. Chem. Soc. 2019, 139, 5474; J. Am. Chem. Soc. 2018, 140, 17007; Organometallics 2019, 38, 3860; J. Am. Chem. Soc. 2020, 142, 10534). Herein, studies are extended to multi-substituted olefins with the goal of evaluating the effect of olefin substitution pattern and substituent identity on selectivity and turnover frequency. The influence of olefin substitution is probed by comparing the conversion of benzene to alkenyl arenes with ethylene, propylene, 1-butene, cis-2-butene, trans-2-butene, isobutene, 2-methyl-2-butene, and tetramethylethylene as well as the phenyl-substituted olefins and isomers of propenylbenzene. The rate of oxidative hydrophenylation for multi-substituted olefins follows the trend monosubstituted > disubstituted > trisubstituted, and tetrasubstituted olefins are unreactive. To probe the effect of substituent size on Markovnikov/ anti-Markovnikov regioselectivity, cyclohexyl, tert-butyl, isopropyl, ethyl, and methyl substituted α-olefins are compared. Selectivity for anti-Markovnikov products generally increases as substituent steric bulk is increased. Tolerance for some functionalized olefins is demonstrated. Here, the ortho/meta/para regioselectivity with mono-substituted arenes reveals that arene and olefin identity influences selectivity. Further mechanistic studies provide evidence for Curtin–Hammet control of ortho/meta/para regioselectivity with monosubstituted arenes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi-Layered CLM (CLM-ML)

This study updates the multi-layered Community Land Model (CLM-ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO 2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi-layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO 2 , temperature, and wind speed) under the canopy. In the single-layer models (CLM4.5 and CLM5), excessive day-to-night differences in leaf temperature and leaf wetness were originally noted, but CLM-ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub-canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM-ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗