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At least 595 records · Page 33

Reduced Order Model of Transactive Bidding Loads

Transactive energy (TE) has been identified to provide better grid efficiency and reliability by market-based transactive exchanges between energy producers and energy consumers. Simulations of TE systems are crucial to evaluate the benefits and impacts of different transactive mechanisms. However, such simulations can be time consuming due to the information exchange between various participants and complex co-simulation environments. In this paper, we develop a reduced order model to speed up the simulation of transactive systems in TE simulation platform (TESP) while achieving very low error between the reduced order and full model results. Specifically, the developed reduced order model consists of an aggregate responsive load agent which utilizes two Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTMs) to enable transactive elements to collectively participate in the TE system. The proposed aggregate responsive load (ARL) agent is able to produce similar transactive behaviors to the full simulation model while achieving significant simulation time reduction. Finally, we also show that the developed model enables generalization of simulation results across different dates and across different number of loads included in the simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simultaneous shape and topology optimization of inflatable soft robots

Simultaneous shape and topology optimization is used to design pressure-activated inflatable soft robots. The pressure loaded boundary is meshed conformingly and shape optimized, while the morphology of the robot is topology optimized. The design objective is to exert maximum force on an object, i.e. to produce soft “grippers”. The robot’s motion is modeled using nearly incompressible finite deformation hyperelasticity. To ensure stability of the robot, the buckling load factors obtained via linearized buckling analyses are constrained. The finite element method is used to evaluate the optimization cost and constraint functions and the adjoint method is employed to compute their sensitivities. The numerical examples produce pressure-driven soft robots with varying complexity. We also compare our simultaneous optimization results to those obtained via sequential topology and then shape optimization.

42 ENGINEERING↗

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗

Investigating size effects of complex nanostructures through Young-Laplace equation and finite element analysis

Analytical studies on the size effects of a simply-shaped beam fixed at both ends have successfully explained the sudden changes of effective Young's modulus as its diameter decreases below 100 nm. Yet they are invalid for complex nanostructures ubiquitously existing in nature. In accordance with a generalized Young-Laplace equation, one of the representative size effects is transferred to non-uniformly distributed pressure against an external surface due to the imbalance of inward and outward loads. Because the magnitude of pressure depends on the principal curvatures, iterative steps have to be adopted to gradually stabilize the structure in finite element analysis. Computational results are in good agreement with both experiment data and theoretical prediction. Furthermore, the investigation on strengthened and softened Young's modulus for two complex nanostructures demonstrates that the proposed computational method provides a general and effective approach to analyze the size effects for nanostructures in arbitrary shape.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

THF co-solvent pretreatment prevents lignin redeposition from interfering with enzymes yielding prolonged cellulase activity

Background: Conventional aqueous dilute sulfuric acid (DSA) pretreatment of lignocellulosic biomass facilitates hemicellulose solubilization and can improve subsequent enzymatic digestibility of cellulose to fermentable glucose. However, much of the lignin after DSA pretreatment either remains intact within the cell wall or readily redeposits back onto the biomass surface. This redeposited lignin has been shown to reduce enzyme activity and contribute to rapid enzyme deactivation, thus, necessitating significantly higher enzyme loadings than deemed economical for biofuel production from biomass. Results: In this study, we demonstrate how detrimental lignin redeposition on biomass surface after pretreatment can be prevented by employing Co-solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment that uses THF–water co-solvents with dilute sulfuric acid to solubilize lignin and overcome limitations of DSA pretreatment. We first find that enzymatic hydrolysis of CELF-pretreated switchgrass can sustain a high enzyme activity over incubation periods as long as 5 weeks with enzyme doses as low as 2 mg protein/g glucan to achieve 90% yield to glucose. A modified Ninhydrin-based protein assay revealed that the free-enzyme concentration in the hydrolysate liquor, related to enzyme activity, remained unchanged over long hydrolysis times. DSA-pretreated switchgrass, by contrast, had a 40% drop in free enzymes in solution during incubation, providing evidence of enzyme deactivation. Furthermore, measurements of enzyme adsorption per gram of lignin suggested that CELF prevented lignin redeposition onto the biomass surface, and the little lignin left in the solids was mostly integral to the original lignin–carbohydrate complex (LCC). Scanning electron micrographs and NMR characterization of lignin supported this observation. Conclusions: Enzymatic hydrolysis of solids from CELF pretreatment of switchgrass at low enzyme loadings was sustained for considerably longer times and reached higher conversions than for DSA solids. Analysis of solids following pretreatment and enzymatic hydrolysis showed that prolonged cellulase activity could be attributed to the limited lignin redeposition on the biomass surface making more enzymes available for hydrolysis of more accessible glucan.

09 BIOMASS FUELS↗

3D ion gyro-orbit heat load predictions for NSTX-U

Abstract High power tokamaks operate with divertor heat loads capable of destroying the plasma facing components (PFCs). High fidelity heat load predictions are necessary to ascertain the PFC state for design and during operation. Typical heat flux calculations are 2D, time invariant, and assume that power flows directly along the magnetic field lines (the optical approximation). These assumptions neglect the complex 3D geometries employed to protect the PFCs, the time varying nature of the plasma and PFC thermal state, and the helical trajectories of ions with finite Larmor radii (the gyro-orbit approximation). An integrated software framework, the heat flux engineering analysis toolkit (HEAT), was developed to generate time varying optical heat loads applied to real engineering computer aided design (CAD) (Looby et al 2022 Fusion Sci. Technol. 78 10–27). Recently, an ion-gyro orbit module has been added to HEAT. This module calculates the helical trajectories of ions as they gyrate about the magnetic field lines using kinetic theory macro-particles to accelerate the calculation. First, the new gyro-orbit module will be presented. Next, a comparison to existing research is performed. Finally, an analysis of the gyro-orbit heat loads for NSTX-U is presented for diverted discharges using the engineering CAD models utilized for PFC fabrication. Including these gyro-orbit effects can enhance the PFC performance by ‘smearing’ out the magnetic shadows associated with the castellated fish-scaled geometry. Simultaneously, the helical trajectories can degrade performance when they load narrow regions on edges and corners with high heat fluxes. Analysis of the trade-offs between these competing effects is included, and regions for further investigation are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗

Efficient Modeling of Floating Wind Arrays Including Current Loads and Seabed Bathymetry: Preprint

Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasistatic solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.

bathymetry↗

Triplet Fusion Upconversion for Photocuring 3D-Printed Particle-Reinforced Composite Networks

High energy photons (λ < 400 nm) are frequently used to initiate free radical polymerizations to form polymer networks, but are only effective for transparent objects. This phenomenon poses a major challenge to additive manufacturing of particle-reinforced composite networks since deep light penetration of short-wavelength photons limits the homogeneous modification of physicochemical and mechanical properties. Herein, the unconventional, yet versatile, multiexciton process of triplet–triplet annihilation upconversion (TTA-UC) is employed for curing opaque hydrogel composites created by direct-ink-write (DIW) 3D printing. TTA-UC converts low energy red light (λ max = 660 nm) for deep penetration into higher-energy blue light to initiate free radical polymerizations within opaque objects. Further, as proof-of-principle, hydrogels containing up to 15 wt.% TiO 2 filler particles and doped with TTA-UC chromophores are readily cured with red light, while composites without the chromophores and TiO 2 loadings as little as 1–2 wt.% remain uncured. Importantly, this method has wide potential to modify the chemical and mechanical properties of complex DIW 3D-printed composite polymer networks.

36 MATERIALS SCIENCE↗

Salt‐in‐Salt Reinforced Carbonate Electrolyte for Li Metal Batteries

Abstract The instability of carbonate electrolyte with metallic Li greatly limits its application in high‐voltage Li metal batteries. Here, a “salt‐in‐salt” strategy is applied to boost the LiNO 3 solubility in the carbonate electrolyte with Mg(TFSI) 2 carrier, which enables the inorganic‐rich solid electrolyte interphase (SEI) for excellent Li metal anode performance and also maintains the cathode stability. In the designed electrolyte, both NO 3 − and PF 6 − anions participate in the Li + ‐solvent complexes, thus promoting the formation of inorganic‐rich SEI. Our designed electrolyte has achieved a superior Li CE of 99.7 %, enabling the high‐loading NCM811||Li (4.5 mAh cm −2 ) full cell with N/P ratio of 1.92 to achieve 84.6 % capacity retention after 200 cycles. The enhancement of LiNO 3 solubility by divalent salts is universal, which will also inspire the electrolyte design for other metal batteries.

Liu, Sufu↗

Salt‐in‐Salt Reinforced Carbonate Electrolyte for Li Metal Batteries

Abstract The instability of carbonate electrolyte with metallic Li greatly limits its application in high‐voltage Li metal batteries. Here, a “salt‐in‐salt” strategy is applied to boost the LiNO 3 solubility in the carbonate electrolyte with Mg(TFSI) 2 carrier, which enables the inorganic‐rich solid electrolyte interphase (SEI) for excellent Li metal anode performance and also maintains the cathode stability. In the designed electrolyte, both NO 3 − and PF 6 − anions participate in the Li + ‐solvent complexes, thus promoting the formation of inorganic‐rich SEI. Our designed electrolyte has achieved a superior Li CE of 99.7 %, enabling the high‐loading NCM811||Li (4.5 mAh cm −2 ) full cell with N/P ratio of 1.92 to achieve 84.6 % capacity retention after 200 cycles. The enhancement of LiNO 3 solubility by divalent salts is universal, which will also inspire the electrolyte design for other metal batteries.

25 ENERGY STORAGE↗

Development and case study of the liquid desiccant system module in sorption system simulation program (SorpSim)

Liquid desiccant systems (LDS) have recently seen an increase in research interest as they can utilize low-grade heat resources and separate the sensible and latent cooling loads by efficiently removing moisture in the air without cooling it to the dew point. Yet, simulation and analysis of LDS had remained complex and demanding due to the limited resources of LDS simulation tools. This work presents the new LDS module developed in the Sorption system Simulation program (SorpSim), which is an open-source and flexible platform for steady-state simulation and analysis of various sorption systems. First, the new LDS module containing a finite-difference model and an effectiveness-NTU model for the heat and mass transfer in LDS dehumidifier/regenerator component was introduced. Then the simulation results of the new module were verified using data from the literature. Lastly, a case study was carried out in SorpSim where an LDS cycle was built and simulated using the new module. The impacts of design and operating parameters on the simulated LDS performance were investigated. The parametric study revealed that a high source temperature improved moisture removal rate (MRR) but reduced the system coefficient of performance (COP); the COP increased monotonically with the desiccant solution recirculation ratio, while the MRR peaked at a ratio of 85%; and an internal solution heat exchanger with UA of 800 W/K was found to be sufficient for optimal performance under high recirculation ratios. The case study demonstrated the LDS module’s capability to facilitate the analysis of LDS design and operation. The LDS module can be further coupled with other component models in SorpSim to simulate and analyze various liquid-desiccant-based systems.

42 ENGINEERING↗

Poromechanical cohesive interface element with combined Mode I-II cohesive zone elastoplasticity for simulating fracture in fluid-saturated porous media

A combined Mode I-II cohesive zone (CZ) elasto-plastic constitutive model, and a two-dimensional (2D) cohesive interface element (CIE) are formulated and implemented at small strain within an ABAQUS User Element (UEL) for simulating 2D crack nucleation and propagation in fluid-saturated porous media. Here, the CZ model mitigates problems of convergence for the global Newton-Raphson solver within ABAQUS, which when combined with a viscous stabilization procedure allows for simulation of post-peak response under load control for coupled poromechanical finite element analysis, such as concrete gravity dam stability analysis. Verification examples are presented, along with a more complex ambient limestone-concrete wedge fracture experiment, water-pressurized concrete wedge experiment, and concrete gravity dam stability analyses. A calibration procedure for estimating the CZ parameters is demonstrated with the limestone-concrete wedge fracture process. For the water-pressurized concrete wedge fracture experiment it is shown that the inherent time-dependence of the poromechanical CIE analysis provides a good match with experimental force versus displacement results at various crack mouth opening rates, yet misses the pore water pressure evolution ahead of the crack tip propagation. This is likely a result of the concrete being partially-saturated in the experiment, whereas the finite element analysis assumes fully water saturated concrete. For the concrete gravity dam analysis, it is shown that base crack opening and associated water uplift pressure leads to a reduced Factor of Safety, which is confirmed by separate analytical calculations.

97 MATHEMATICS AND COMPUTING↗

Dependence of the kinetic energy absorption capacity of bistable mechanical metamaterials on impactor mass and velocity

Using an alternative mechanism to dissipation or scattering, bistable structures and mechanical metamaterials have shown promise for mitigating the detrimental effects of impact by reversibly locking energy into strained material. Herein, we extend prior works on impact absorption via bistable metamaterials to computationally explore the dependence of kinetic energy transmission on the velocity and mass of the impactor, with strain rates exceeding 10 2 s –1 . We observe a large dependence on both impactor parameters, ranging from significantly better to worse performance than a comparative linear material. We then correlate the variability in performance to solitary wave formation in the system and give analytical estimates of idealized energy absorption capacity under dynamic loading. In addition, we find a significant dependence on damping accompanied by a qualitative difference in solitary wave propagation within the system. The complex dynamics revealed in this study offer potential future guidance for the application of bistable metamaterials to applications including human and engineered system shock and impact protection devices.

42 ENGINEERING↗

Examining and Modeling Oxygen Uncoupling Kinetics of Cu-Based Oxygen Carriers for Chemical Looping with Oxygen Uncoupling (CLOU) in a Drop Tube Fluidized Bed Reactor

Chemical looping combustion with oxygen uncoupling (CLOU) is a promising carbon capture and storage (CCS) technology for conversion of gaseous and solid hydrocarbon fuels where the release of gaseous O 2 from an oxygen carrier is favored at high temperature and low O 2 partial pressure. One promising CLOU material is the copper oxide redox system (CuO–Cu 2 O). The primary objective of this study was to examine the use of a drop tube fluidized bed reactor (DT-FBR) for evaluating the kinetics of oxygen uncoupling with Cu-based oxygen carriers. Appropriate rate expressions from redox experiments are needed to model and scale up CLOU systems. Additionally, the determined oxygen uncoupling kinetic parameters were validated using a computational fluid dynamic model. Two oxygen carriers consisting of 20 wt % CuO/Al 2 O 3 and 9 wt % CuO/Al 2 O 3 were prepared by physical mixing. A third oxygen carrier sample was prepared at 9 wt % CuO/Al 2 O 3 by incipient wetness impregnation. The reaction rates of the copper oxide redox system are strongly dependent on thermodynamic effects of the oxygen partial pressure relative to the equilibrium oxygen partial pressure. The results presented in this paper offer an alternative and simplified kinetic analysis compared to that traditionally presented in the literature for the thermal reduction of copper oxide or other CLOU oxygen carriers. The reactor system used in this study allows for operating parameters to be adjusted, minimizing thermodynamic and mass transfer limitations, which eliminates the need for more complex kinetic/thermodynamic reaction models. The reaction kinetics measured in this study is compared based on the preparation method and the CuO weight percent loading. These results may aid in the development of CLOU technologies during reactor design and process modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pt Particles on a Dynamic TiO 2 Support in Near-Ambient Conditions−Disentangling Size, Pressure, and Support Effects

Platinum particles on reducible oxides are known to form complex and highly dynamic catalyst systems at elevated pressures and temperatures, often adopting active structures that differ from those found at room temperature and under ultrahigh vacuum (UHV). Here, we study the oxidation and structural evolution of subnanometer Pt clusters and nanoparticles supported on rutile TiO 2 (110) across an oxygen pressure range from UHV to 0.1 mbar, using near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS), scanning tunneling microscopy (STM) under UHV and NAP conditions, and low-energy ion scattering (LEIS). Our results reveal distinct differences in oxidation behavior and thermal stability between Pt nanoparticles and clusters, which are further modulated by the support stoichiometry and oxygen pressure. Small Pt clusters become oxidized even at room temperature but are susceptible to accelerated sintering in 0.1 mbar O 2 at elevated temperatures. In contrast, well-crystallized Pt nanoparticles on near-stoichiometric TiO 2 show weaker oxidation. On a reduced, defective TiO 2 support, Pt instead quickly becomes deeply buried by new titania layers, which are formed during support reoxidation. This process appears to result primarily from interactions of the support with the gas phase, unlike the classical, selflimited encapsulation that is induced by the strong metal−support interaction (SMSI). Finally, we address the full complexity of real catalysts in a direct side-by-side comparison of the single-crystalline model system with a Pt-loaded TiO 2 powder catalyst (P25). We conclude that the stoichiometry of the model supports must be carefully chosen and controlled to accurately reproduce the expected state of powder supports during redox reactions.

metal nanoparticles↗

Control of hierarchical polymer mechanics with bioinspired metal-coordination dynamics

In conventional polymer materials, mechanical performance is traditionally engineered via material structure, using motifs such as polymer molecular weight, polymer branching, or copolymer-block design1. Here, by means of a model system of 4-arm poly(ethylene glycol) hydrogels crosslinked with multiple, kinetically distinct dynamic metal-ligand coordinate complexes, we show that polymer materials with decoupled spatial structure and mechanical performance can be designed. By tuning the relative concentration of two types of metal-ligand crosslinks, we demonstrate control over the material’s mechanical hierarchy of energy-dissipating modes under dynamic mechanical loading, and therefore the ability to engineer a priori the viscoelastic properties of these materials by controlling the types of crosslinks rather than by modifying the polymer itself. This strategy to decouple material mechanics from structure may inform the design of soft materials for use in complex mechanical environments.

36 MATERIALS SCIENCE↗

Single-atom gold oxo-clusters prepared in alkaline solutions catalyse the heterogeneous methanol self-coupling reactions

We report the direct use of inorganometallic gold complexes formed in alkaline solutions as robust heterogeneous catalysts. Specifically, mononuclear gold complexes with the gold atom surrounded by a shell of Na cations through -O- linkages were prepared by dissolving Au(OH) 3 in highly alkaline solutions of NaOH. The complexes remain intact upon impregnation onto supports or after drying in air to a crystalline powder. Supported catalysts containing exclusively atomic gold at loadings up to 1.2 wt.% Au were prepared. Either in supported or unsupported form, the mononuclear gold-centered oxo-clusters catalyze the selective methanol dehydrogenation reaction to methyl formate (MF) and hydrogen; a reaction of industrial interest as well as the key step in methanol steam reforming. The [Au1-Ox]- center was identified as the active catalytic site by experimental characterization and density functional theory studies. The methanol dehydrogenation reaction mechanism proceeds via the self-coupling of methanol to MF. No oxygen supply is necessary. Hence, hydrogen rather than water is produced at 2:1 (stoichiometric) molar ratio to MF. The dried crystalline powder of the solution was used as an unsupported catalyst, showing the same chemistry as the supported clusters. Ab initio molecular dynamics (AIMD) simulations of methanol self-coupling on the mononuclear gold clusters revealed the formation of formate spectators on the clusters under reaction conditions, also corroborated by in situ DRIFTS. The inclusion of these spectators proved crucial towards the accurate description of the energetics of self-coupling of methanol on these clusters, thus unravelling the nature of the active site. Catalyst stability up to 250-300 oC in reaction conditions is demonstrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗