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At least 685 records · Page 38

Cloud droplet diffusional growth in homogeneous isotropic turbulence: bin microphysics versus Lagrangian super-droplet simulations

The increase in the spectral width of an initially monodisperse population of cloud droplets in homogeneous isotropic turbulence is investigated by applying a finite-difference fluid flow model combined with either Eulerian bin microphysics or a Lagrangian particle-based scheme. The turbulence is forced applying a variant of the so-called linear forcing method that maintains the mean turbulent kinetic energy (TKE) and the TKE partitioning between velocity components. The latter is important for maintaining the quasi-steady forcing of the supersaturation fluctuations that drive the increase in the spectral width. We apply a large computational domain (64 3 m 3 ), one of the domains considered in Thomas et al. (2020). The simulations apply 1 m grid length and are in the spirit of the implicit large eddy simulation (ILES), that is, with small-scale dissipation provided by the model numerics. This is in contrast to the scaled-up direct numerical simulation (DNS) applied in Thomas et al. (2020). Two TKE intensities and three different droplet concentrations are considered. Analytic solutions derived in Sardina et al. (2015), valid for the case when the turbulence integral timescale is much larger than the droplet phase relaxation timescale, are used to guide the comparison between the two microphysics simulation techniques. The Lagrangian approach reproduces the scalings relatively well. Representing the spectral width increase in time is more challenging for the bin microphysics because appropriately high resolution in the bin space is needed. The bin width of 0.5 µm is only sufficient for the lowest droplet concentration (26 cm -3 ). For the highest droplet concentration (650 cm -3 ), an order of magnitude smaller bin size is barely sufficient. The scalings are not expected to be valid for the lowest droplet concentration and the high-TKE case, and the two microphysics schemes represent similar departures. Finally, because the fluid flow is the same for all simulations featuring either low or high TKE, one can compare point-by-point simulation results. Such a comparison shows very close temperature and water vapor point-by-point values across the computational domain and larger differences between simulated mean droplet radii and spectral width. The latter are explained by fundamental differences in the two simulation methodologies, numerical diffusion in the Eulerian bin approach and a relatively small number of Lagrangian particles that are used in the particle-based microphysics.

54 ENVIRONMENTAL SCIENCES↗

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

w Mel replacement of dengue-competent mosquitoes is robust to near-term climate change

Rising temperatures are impacting the range and prevalence of mosquito-borne diseases. A promising biocontrol technology replaces wild mosquitoes with those carrying the virus-blocking Wolbachia bacterium. Because the most widely used strain, wMel, is adversely affected by heat stress, we examined how global warming may influence wMel-based replacement. We simulated interventions in two locations with successful field trials using Coupled Model Intercomparison Project Phase 5 climate projections and historical temperature records, integrating empirical data on wMel’s thermal sensitivity into a model of Aedes aegypti population dynamics to evaluate introgression and persistence over one year. We show that in Cairns, Australia, climatic futures necessitate operational adaptations for heatwaves exceeding two weeks. In Nha Trang, Vietnam, projected heatwaves of three weeks and longer eliminate wMel under the most stringent assumptions of that symbiont’s thermal limits. We conclude that this technology is generally robust to near-term (2030s) climate change. Accelerated warming may challenge this in the 2050s and beyond.

54 ENVIRONMENTAL SCIENCES↗

Characterization of runaway electron impact on instrumented sacrificial limiters on DIII-D

Instrumented sacrificial limiter heads, both domed (proud) and flat (flush) are used in DIII-D runaway electron (RE) wall strikes to study the wall impact dynamics with high spatial and time resolution. The approximate structure of the RE wetted area and heating depth on the domed limiter heads were predicted qualitatively using orbit-tracking simulations, although a strong left–right asymmetry (about the magnetic field direction) was not captured well by the simulations. It is hypothesized that this difference is perhaps due to the local 3D magnetic field perturbation of the dome limiter head. The average kinetic energy K and pitch angle θ of REs striking the limiter head were estimated from the spatial distribution of local HXR emission and were estimated to be roughly K ≈ 4 MeV and θ ≈ 0.2 rad. These values are roughly consistent with in-plasma values estimated before the loss event, indicating that RE kinetic energy and pitch angle are not drastically altered when transporting to the wall. Large shot–shot variations (1–10 kJ) in energy deposition into the limiter head were observed and were explained by shot–shot variations in locked magneto-hydrodynamics mode toroidal phase. For the largest deposited energies (10 kJ), graphite material failure and explosive dust release was observed, and the depth of material failure at higher energy deposition was successfully reproduced using modelling of volumetric energy deposition and brittle failure. The presence of energetic (keV) level ion impact during the RE wall strike was confirmed by three different surface analysis techniques. The ratio of energetic ion to RE flux appears to be larger on flat surfaces within the RE wetted area, although the energetic ion flux and total energy flux due to energetic ions have not yet been quantified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding Reentrance in Frustrated Magnets: The Case of the Er 2 Sn 2 O 7 Pyrochlore

Reentrance, the return of a system from an ordered phase to a previously encountered less-ordered one as a controlled parameter is continuously varied, is a recurring theme found in disparate physical systems, yet its microscopic cause is often not investigated thoroughly. Here, through detailed characterization and theoretical modeling, we uncover the microscopic mechanism behind reentrance in the strongly frustrated pyrochlore antiferromagnet Er 2 Sn 2 O 7 . We use single crystal heat capacity measurements to expose that Er 2 Sn 2 O 7 exhibits multiple instances of reentrance in its magnetic field B vs temperature T phase diagram for magnetic fields along three cubic high symmetry directions. Through classical Monte Carlo simulations, mean field theory, and classical linear spin-wave expansions, we argue that the origins of the multiple occurrences of reentrance observed in Er 2 Sn 2 O 7 are linked to soft modes. These soft modes arise from phase competition and enhance thermal fluctuations that entropically stabilize a specific ordered phase, resulting in an increased transition temperature for certain field values and thus the reentrant behavior. Our work represents a detailed examination into the mechanisms responsible for reentrance in a frustrated magnet and may serve as a template for the interpretation of reentrant phenomena in other physical systems.

36 MATERIALS SCIENCE↗

Stable and unstable tiling patterns formed by ABC miktoarm star triblock terpolymers of symmetric interactions

Several discrepancies exist among previous self-consistent field calculations of symmetrically interacting ABC miktoarm star triblock terpolymer melts. Here we address this issue by including all known tiling patterns, as well as several lamellar-type phases known to bound the regions in the parameter space occupied by these patterns. After carefully studying the effect of numerical parameters on the free-energy accuracy, the central region of the phase diagram is constructed in detail; both the (3.4.6.4) pattern and the three-dimensional phase of hierarchical-hexagonal lamellae are found to be stable for the first time. The energetic and entropic contributions to the free-energy density of several phases are analyzed and compared in detail to reveal their stability mechanisms, including the important ( 3 2 .4.3.4) pattern. Comparisons to previous studies of the same model system are present throughout, with our results resolving the aforementioned discrepancies and providing a sound basis for future work to build upon. Published by the American Physical Society 2024

Materials Science↗

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗

Single-Phase Dielectric Fluid Thermal Management for Power-Dense Automotive Power Electronics

This paper describes the design and performance of a dielectric fluid cooling concept for automotive power electronics. The concept combines a low-thermal-resistance package (which eliminates metalized ceramic substrates) with a high-performance convective cooling strategy (slot jets impinging on finned surfaces). Modeling was first used to design the cooling system to maximize thermal performance and minimize pumping power. Additionally, a prototype was then fabricated, and experiments were conducted to validate the model predictions using three fluids at various fluid flow rates (16.7 cm 3 /s [1 L/min] to 68.3 cm 3 /s [4.1 L/min]) and inlet temperatures (30C and 70C). The final design was compact (120-cm 3 total volume, including heat exchanger and conceptual power modules) and cooled 12 devices (e.g., silicon carbide). The validated model was then used to predict the junction-to-fluid thermal resistance and pumping power for various conditions, including 40C fluid temperature. The results predict thermal resistance values as low as 19 mm 2 K/W are possible using the dielectric fluid cooling approach. The dielectric fluid cooling system is predicted to provide thermal resistance and pumping power values that are approximately 56% and 90% lower, respectively, compared to an automotive power electronics cooling system.

30 DIRECT ENERGY CONVERSION↗

Phase change material integrated core–shell catalyst for in situ thermal control in methanol synthesis from syngas

A model-guided core–shell catalyst design is presented for methanol synthesis, featuring a phase change material (PCM) core encapsulated by a Cu–Zn–Al 2 O 3 (CZA) catalytic shell. The PCM enables in situ thermal management by absorbing reaction heat at its melting point, mitigates the kinetic decline at high temperatures and therefore avoids low conversion, prevents hot spots, and stabilizes the reaction temperature. A two-dimensional axisymmetric, non-isothermal packed-bed reactor model (COMSOL 6.3) was developed for a 10 g system. Simulations evaluate three PCM candidates, that is, LiNO 3 , 9 wt% LiCl + 91 wt% LiNO 3 , and commercial H250, with melting points near 244–250°C. Results indicate that CO conversion can increase from 34.4% to 52.4%, and methanol production can improve by 69% compared to a conventional packed-bed reactor. Beyond methanol synthesis, the PCM-integrated core–shell concept provides a scalable approach for thermal control in exothermic reactions, improving reactor efficiency and safety.

core–shell catalyst↗

Phase-field modeling of thermally-grown oxide and damage evolution in environmental barrier coatings

Silicon carbide-based ceramic matrix composites protected by environmental barrier coatings (EBCs) present a promising materials solution for next-generation gas turbines. Developing more robust and efficient EBCs is therefore of significant technological importance. During the service in high-temperature oxidative environments, there is a thermally grown oxide (TGO) layer, spontaneously formed in the EBC system. TGO is recognized as a critical factor for the degradation and failure of EBCs, yet the detailed mechanisms of TGO growth and its effect on EBC failure remain unclear. In this study we develop a comprehensive chemo-mechano-phase-field model to simulate growth of the TGO in EBCs, factoring in creep and deformation, and especially the cracking behaviors. The volume expansion due to TGO growth and the resulting large inelastic deformation are addressed by using our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm, in combination with an adapted Hu-Chen spectral solver for elasticity. Simulations of TGO growth are performed considering different growth modes of TGOs determined mainly by the ratio of oxidant permeability in the topcoat to that in the TGO itself. Large-scale three-dimensional (3D) simulations are performed to model the formation of interconnecting vertical/channel cracks (often called ‘mud cracks’). The simulated crack morphology are in excellent agreement with the experimental observations from the literature. The simulations also provide insights into the cracking of EBCs and its dependence on the structure and constituent properties of the coating system. Furthermore, these results demonstrate the developed damage model can be a useful tool for design of more durable EBCs.

Cracking↗

Modeling of hepatitis B virus infection spread in primary human hepatocytes

ABSTRACT Chronic hepatitis B virus (HBV) infection poses a significant global health threat, causing severe liver diseases including cirrhosis and hepatocellular carcinoma. We characterized HBV DNA kinetics in primary human hepatocytes (PHHs) over 32 days post-inoculation (p.i.) and modified ourin-vivoagent-based modeling (ABM) to gain insights into the HBV lifecycle and spreadin vitro. Parallel PHH cultures were mock-treated or treated with HBV entry inhibitor Myr-preS1 (6.25 µg/mL) was initiated 24 h p.i. In untreated PHH, three viral DNA kinetic patterns were identified: (i) an initial decline, followed by (ii) rapid amplification and (iii) slower amplification/accumulation. In the presence of Myr-preS1, viral DNA and infected cell numbers in phase 3 were effectively blocked, with minimal to no increase. This suggests that phase 2 represents viral amplification in initially infected cells, while phase 3 corresponds to viral spread to naïve cells. The ABM reproduced well the HBV kinetic patterns observed and predicted that the viral eclipse phase lasts between 18 and 38 h. After the eclipse phase, the viral production rate increased over time, starting with a slow production cycle of 1 virion per day, which gradually accelerated to 1 virion per hour after 3 days. Approximately 4 days later, virion production reached a steady state production rate of 4 virions/h. The estimated median efficacy of Myr-preS1 in blocking HBV spread was 91% (range: 90–92%). The HBV kinetics and the predicted estimates of the HBV eclipse phase duration and HBV production cycles in PHH are similar to those predicted in uPA/SCID mice with human livers. IMPORTANCE While primary human hepatocytes (PHHs) are the most physiologically relevant culture system for studying HBV infectionin vitro, a comprehensive understanding of HBV infection kinetics and spread in PHH is lacking. In this study, we characterize HBV viral kinetics and modify ourin vivoagent-based modeling (ABM) to provide quantitative insights into the HBV production cycle and viral spread in PHH. The ABM provides an estimate of the HBV eclipse phase duration, HBV production cycles, and Myr-preS1 efficacy in blocking HBV spread in PHH. The results resemble those predicted in uPA/SCID mice with human livers, demonstrating that estimated HBV infection kinetic parameters in PHHin vitromirror those observed in thein vivoHBV infection chimeric mouse model.

Virology↗

Global Gas-Phase Oxidation Rates of Select Products from the Fast Pyrolysis of Lignocellulose

The oxidation kinetics for products of fast pyrolysis at low temperatures (<600°C) are not well known. These will be important in effort to model autothermal pyrolysis, which has been recently developed to intensify the process, but which occurs at much lower temperatures than combustion. Furthermore, this study determines global oxidation rates at 400-600°C for three important products of fast pyrolysis: levoglucosan, xylose, and acetic acid. Experiments were performed in a fluidized bed pyrolyzer with the reactor modeled as a series of CSTRs and PFRs to determine reaction rates. Oxidation rates at 500°C for the three model compounds varied by a factor of ten.

09 BIOMASS FUELS↗

Real-Time Atomic-Scale Structural Analysis Resolves the Amorphous to Crystalline CaCO 3 Mechanism Controversy

Amorphous calcium carbonate (ACC) occurs as a precursor to geological and biogenic calcium carbonate (CaCO 3 ), yet its transformation pathways and reaction mechanisms remain inconsistent and controversial. In this study, we investigated the transformation of ACC to calcite under both solution and dry conditions, in the presence and absence of impurity ions, utilizing operando time-resolved synchrotron X-ray diffraction (TRXRD) and reactive transport modeling. Results demonstrate that TRXRD techniques allow us to differentiate dissolution-reprecipitation versus solid-state transformation mechanisms for amorphous to crystalline phase transitions. Specifically, we observe that in environments with abundant water, ACC transforms to calcite through a dissolution-reprecipitation mechanism. This features an activation energy of 63 ± 2 kJ/mol and unit cell volume contraction during calcite crystal growth. Conversely, under water-limited conditions, ACC to calcite transformation proceeds via a solid-state transformation mechanism, with an activation energy of 210 ± 2 kJ/mol, three times greater than the dissolution-reprecipitation route, and a unit cell expansion during crystalline calcite growth. Further, to illustrate the magnitude of these effects, the rates of calcite growth were similar during dissolution-reprecipitation at 3 °C [0.00207(35) s –1 ] and solid-state transformation at 280 °C [0.00134(11) s –1 ]. Moreover, the incorporation of an impurity, strontium, significantly retards the rate of calcite growth while expanding its unit cell but whose incorporation is history dependent. Reactive transport modeling of the dissolution–precipitation kinetics suggests that ACC must be dissolving as compact aggregates. These various transformation mechanisms drive diverse geological and biological carbonate formations, impacting their use as paleoenvironmental markers and functional materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evidence from transport measurements for YRh 6 Ge 4 being a triply degenerate nodal semimetal

We have investigated magnetotransport properties of YRh 6 Ge 4 , which was recently predicted to be a triply degenerate nodal semimetal. We find it exhibits remarkable signatures of a chiral anomaly, manifested by large negative longitudinal magnetoresistance, the quadratic field dependence of magnetoconductance and the planar Hall effect. Furthermore, we have also observed Shubnikov-de Haas (SdH) quantum oscillations in the magnetoresistivity measurements on this material. The analyses of the SdH data reveal two pointlike Fermi surfaces and these pockets are found to host nearly massless fermions. The small size of these Fermi pockets is in a good agreement with the theoretical prediction that the triply degenerate point in YRh 6 Ge 4 is much closer to the Fermi level than previously demonstrated triply degenerate nodal semimetals such as MoP and WC. These results suggest YRh 6 Ge 4 may serve as a model system to probe exotic properties of three-component fermions and understand their underlying physics.

36 MATERIALS SCIENCE↗

A novel shallow bore ground heat exchanger for ground source heat pump applications—Model development and validation

A novel ground heat exchanger design, the Underground Thermal Battery (UTB), was proposed as a low-cost alternative to the conventional vertical bore ground heat exchanger (VBGHE) for the application of ground source heat pumps (GSHPs). The UTB is designed to be installed in a shallow borehole (less than 6 m deep) and thus could cost much less than the conventional VBGHE, which usually is installed in vertical bores 60 m deep. By utilizing natural convection of water and phase change materials, the UTB tempers its temperature change in response to thermal loads, which helps improve the efficiency of GSHPs. A one-dimensional (1D) model of the UTB has been developed and validated with the measured performance data of a small-scale UTB, as well as the simulation results of a more detailed three dimensional (3D) numerical model, which accounts for both heat transfer and fluid dynamics in the UTB. Further, this 1D model is computationally much more efficient than the 3D model and thus can simulate the annual performance of the UTB with acceptable computation time. The 1D model has been used to evaluate the performance of the UTB so that it can be compared with the conventional VBGHE.

42 ENGINEERING↗