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At least 667 records · Page 37

An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities

An optimization-based design framework is proposed to tune the response of soft metamaterials involving both geometric instabilities and nonlinear viscoelastic material behavior. Designing the response of soft metamaterials to harness instabilities and undergo large, tailored configuration changes will enable advancements in soft robotics, shock and vibration mitigation, and flexible electronics. In line with the metamaterial concept, the response of these materials is governed to a large extent by the geometric and topological makeup of their small-scale features. However, the link between structure and response is less intuitive for soft metamaterials due to their reliance upon highly nonlinear responses triggered by geometric instabilities. This is further complicated by the effects of viscoelastic relaxation, which recent studies have shown to alter the emergence of instabilities in non-intuitive ways. Here, these effects are accounted for in our framework to achieve various design objectives, including tailored force–displacement response and maximized energy absorption from both geometric and material effects. To fully automate this process, it is essential to have a completely robust equation solver for forward problems involving instabilities and viscoelastic relaxation. We achieve this by casting the search for stable mechanical equilibrium — i.e. the forward problem — as a minimization problem and utilize a trust region algorithm to robustly handle instabilities and follow energetically-favorable equilibrium paths through critical points.

97 MATHEMATICS AND COMPUTING↗

Data-driven analysis of relight variability of jet fuels induced by turbulence

For safety purposes, reliable reignition of aircraft engines in the event of flame blow-out is a critical requirement. Typically, an external ignition source in the form of a spark is used to achieve a stable flame in the combustor. However, such forced turbulent ignition may not always successfully relight the combustor, mainly because the state of the combustor cannot be precisely determined. Uncertainty in the turbulent flow inside the combustor, inflow conditions, and spark discharge characteristics can lead to variability in sparking outcomes even for nominally identical operating conditions. Prior studies have shown that of all the uncertain parameters, turbulence is often dominant and can drastically alter ignition behavior. For instance, even when different fuels have similar ignition delay times, their ignition behavior in practical systems can be completely different. In practical operating conditions, it is challenging to understand why ignition fails and how much variation in outcomes can be expected. The focus of this work is to understand relight variability induced by turbulence for two different aircraft fuels, namely Jet-A and a variant named C1. A detailed, previously developed simulation approach is used to generate a large number of successful and failed ignition events. Using this data, the cause of misfire is evaluated based on a discriminant analysis that delineates the difference between turbulent initial conditions that lead to ignition or failure. From the discriminant analysis, a compressed sensing algorithm is then applied to help pinpoint the locations of relevant turbulent features. Findings from the discriminant analysis are confirmed with the time history of near kernel properties. Next, a clustering strategy is used to identify ignition and misfire modes. With this approach, it was determined that the cause of ignition failure is different for the two fuels. While it was found that Jet-A is influenced by fuel entrainment, C1 was found to be more sensitive to small scale turbulence features. Finally, a larger variability is found in the ignition modes of C1, which can be subject to extreme events induced by kernel breakdown.

42 ENGINEERING↗

Adaptive mesh based combustion simulations of direct fuel injection effects in a supersonic cavity flame-holder

Here, we present high-fidelity reacting simulations of a supersonic cavity flame-holder configuration. The focus of this work is on flame stabilization brought about by varying the location of fuel injection in a cavity stabilized supersonic flow of air. Central to our approach is a compressible multi-species reacting flow solver that uses adaptive-mesh-refinement (AMR), enabling the resolution of flame, shock-waves, boundary-layers, and small-scale structures in the computational domain. Our analysis indicates that fuel injection closer to the ramp at the aft end of the cavity allows for greater mixing and lower peak temperatures compared to fuel injection upstream that is closer to the backward facing step of the cavity. This difference is mainly due to greater turbulent fluctuations generated from the shear-layer towards the cavity ramp, thereby enhancing the mixing of fuel and air. A low frequency oscillatory behaviour in heat-release and pressure was also observed for the upstream injection case while a much higher-frequency phenomena was observed in the near-ramp injection case. By identifying the important physical determinants of the combustion processes, this study illustrates a promising pathway to design and optimize direct fuel injection strategies in supersonic cavity flame-holders that can improve flame stability, combustion efficiency, and reduce emissions.

42 ENGINEERING↗

Benchmarking of massively parallel phase-field codes for directional solidification

We present a detailed benchmark comparing two state-of-the-art phase-field implementations for simulating alloy solidification under experimentally relevant conditions. The study investigates the directional solidification of Al-3wt%Cu under high-velocity solidification conditions and SCN-0.46wt% camphor under microgravity conditions from National Aeronautics and Space Administration (NASA) DECLIC-DSI-R experiments. Both codes, one employing finite-difference discretization with uniform mesh and GPU-acceleration (GPU-PF) and the other one employing finite-element discretization with adaptive-mesh and CPU-parallelization (PRISMS-PF), solve the same quantitative phase-field formulation that incorporates an anti-trapping current for the solidification of dilute alloys. We evaluate the predictions of each code for dendritic morphology, primary spacing, and tip dynamics in both 2D and 3D, as well as their numerical convergence and computational performance. While existing benchmark problems have primarily focused on simplified or small-scale simulations, they do not reflect the computational and modeling challenges posed by employing experimentally relevant time and length scales. Our results provide a practical framework for assessing phase-field code performance as well as validating and facilitating their application in integrated computational materials engineering (ICME) workflows that require integration with realistic experimental data.

36 MATERIALS SCIENCE↗

High-Fidelity Simulations of Gravity Currents Using a High-Order Finite-Difference Spectral Vanishing Viscosity Approach

This numerical work investigates the potential of a high-order finite-difference spectral vanishing viscosity approach to simulate gravity currents at high Reynolds numbers. The method introduces targeted numerical dissipation at small scales through altering the discretisation of the second derivatives of the viscous terms in the incompressible Navier-Stokes equations to mimic the spectral vanishing viscosity (SVV) operator, originally designed for the regularisation of spectral element method (SEM) solutions of pure advection problems. Using a sixth-order accurate finite-difference scheme, the adoption of the SVV method is straightforward and comes with a negligible additional computational cost. In order to assess the ability of this high-order finite-difference spectral vanishing viscosity approach, we performed large-eddy simulations (LES) of a gravity current in a channelised lock-exchange set-up with our SVV model and with the well-known explicit static and dynamic Smagorinsky sub-grid scale (SGS) models. The obtained data are compared with a direct numerical simulation (DNS) based on more than 800 million mesh nodes, and with experimental measurements. A framework for the energy budget is introduced to investigate the behaviour of the gravity current. First, it is found that the DNS is in good agreement with the experimental data for the evolution of the front location and velocity field as well as for the stirring and mixing inside the gravity current. Secondly, the LES performed with less than 0.4% of the total number of mesh nodes compared to the DNS, can reproduce the main features of the gravity currents, with the SVV model yielding slightly more accurate results. It is also found that the dynamic Smagorinsky model performs better than its static version. For the present study, the static and dynamic Smagorinsky models are 1.8 and 2.5 times more expensive than the SVV model, because the latter does not require the calculation of explicit SGS terms in the Navier-Stokes equations nor spatial filtering operations.

direct numerical simulation↗

Testing α -attractor quintessential inflation against CMB and low-redshift data

Due to universality and attractor properties, α-attractor quintessential inflation establishes direct relations between inflationary observables such as the scalar tilt n s and the tensor-to-scalar ratio r, and late-time dark energy equation of state parameters w 0 and w a . In this work, we examine three different physically motivated regimes, considering complete freedom in the parameter α, models inspired by supergravity where α takes on values up to α = 7/3, and Starobinsky inflation (α = 1). We investigate the consistency and constraints imposed by Cosmic Microwave Background measurements from the Planck satellite, B-mode polarization data from the BICEP/Keck collaboration, and low-redshift observations. Additionally, we consider small-scale CMB measurements released by the Atacama Cosmology Telescope, which give results approaching the Harrison– Zel’dovich spectrum (n s ≈ 1). Here α-attractors lead to an improved fit over $\Lambda$CDM. For the large-scale CMB measurements, α ≳ 2 models can provide equally good fits as $\Lambda$CDM

79 ASTRONOMY AND ASTROPHYSICS↗

Testing the parametric model for self-interacting dark matter using matched halos in cosmological simulations

Here, we systemically evaluate the performance of the self-interacting dark matter (SIDM) halo model proposed in Ref.Yang et al. (2023) with matched halos from high-resolution cosmological CDM and SIDM simulations. The model incorporates SIDM effects along mass evolution histories of CDM halos and it is applicable to both isolated halos and subhalos. We focus on the accuracy of the model in predicting halo density profiles at z = 0 and the evolution of maximum circular velocity. We find the model predictions agree with the simulations within 10%–50% for most of the simulated (sub)halos, 50%–100% for extreme cases. This indicates that the model effectively captures the gravothermal evolution of the halos with very strong, velocity-dependent self-interactions. For an example application, we apply the model to study the impact of various SIDM scenarios on strong lensing perturber systems, demonstrating its utility in predicting SIDM effects for small-scale structure analyses. Our findings confirm that the model is an effective tool for mapping CDM halos into their SIDM counterparts.

Yang, Daneng [Chinese Academy of Sciences, Nanjing↗

European residential wood pellet trade and prices dataset

The European market for wood pellets used in small-scale heating systems has been expanding significantly over the past decade. For an analysis of market efficiency in the Journal Energy with the title “The European wood pellets for heating market - price developments, trade and market efficiency“ wood pellet prices have been collected as well as trade flows downloaded for the trade relations between Austria, Germany, Italy and France. Only since January 2012 monthly wood pellet trade data is published by Eurostat. This, now monthly expanding data-set provides new opportunities for analysing the development of this important renewable energy commodity. Furthermore, national wood pellet prices published by national authorities and interest groups are improving in quality in the recent years. The collection and combination of these data-sets are a chance for novel econometric analysis. This paper presents valuable tools and processes to acquire and prepare this data and connects to a data and code repository for downloading the resources described in this and the related Journal Energy publication.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Numerical modeling and parametric study of a dual purpose underground thermal battery

We report integrating thermal energy storage with building energy systems can enable flexible building electric demands at buildings to help mitigate the mismatch between electricity supply and demand. A novel building heating and cooling system that integrates a dual-source heat pump with hybrid thermal storage named dual-purpose underground thermal battery (DPUTB) has been developed for reshaping building electric demands. The proposed DPUTB integrated geothermal heat pump system is an original innovation that enables Grid-interactive Energy Efficient buildings. This paper focuses on the study of the novel DPUTB. The DPUTB works as both a thermal storage tank (an inner tank) and a ground heat exchanger (an outer tank separated from the inner tank by the insulation material). High fidelity and computationally effective models are needed to predict the performance of the novel DPUTB. This study has developed a simplified dynamic model for the DPUTB according to heat transfer and energy conservation principles and validated it by using experimental data obtained from testing a small-scale DPUTB apparatus. A parametric study was conducted to identify a design that can achieve the target thermal storage performance of load shift and energy efficiency. The parametric study results show that the inner tank shell thermal conductivity and the phase change material's melting point are the two most influencing factors on the performance of the DPUTB. One single full-size DPUTB with the identified design could provide 1-ton cooling (3.51 kW) with the supply temperature lower than 11 °C for 4 hours in summer after being fully charged in 8 hours. The inner tank filled with phase change material is for cooling thermal storage as a latent tank in the design. However, its capacity can be as high as 60 MJ as a sensible water tank for heating storage in winter. In the future study, the DPUTB model will be incorporated into the dual-source heat pump system for evaluating the overall system performance of demand side management in the long term.

25 ENERGY STORAGE↗

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. We report the simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

30 DIRECT ENERGY CONVERSION↗

Toward more mechanistic representations of biogeochemical processes in river networks: Implementation and demonstration of a multiscale model

A recently introduced multiscale model for representing the effects of small-scale hyporheic-zone biogeochemical processes is extended from the reach scale to river network scales. The model uses advection-dispersion-reaction equations for the channel network and one-dimensional advection-reaction subgrid models for the hyporheic zone. We summarize implementation in the integrated surface/subsurface hydrology modeling system Amanzi-ATS. The extension uses topologically defined meshes to represent stream/river networks and associates a hyporheic subgrid model with each channel grid cell. Biogeochemical reaction modeling capability residing in community software is accessed through an application programming interface. The implementation is verified against independent numerical solutions on a single reach. Mesh convergence studies show that commonly used semi-distributed representations can introduce significant spatial discretization error. Denitrification of farm runoff in a subbasin of the Portage River Basin in Ohio, USA is used to demonstrate the general-purpose reactive transport capability.

54 ENVIRONMENTAL SCIENCES↗

Forensic species identification of elasmobranchs landed in Costa Rican artisanal fisheries

Elasmobranchs represent one of the most imperiled taxa, yet few nations have developed catch limits and no international or bilateral catch limits exist. One barrier to establishing catch limits is a lack of accurate species-specific extraction rates due to many species looking similar, distinguishing characteristics (fins and head) being removed, or grouping of all elasmobranchs together in fisheries data. To better understand the species-specific impacts fisheries are having on elasmobranchs we used forensic genetic techniques to identify the types and quantities of shark species landed in Costa Rican artisanal small-scale and mid-scale fisheries. We collected elasmobranch tissue samples from fishermen in three locations along Costa Rica’s Pacific Coast: Coyote, Bejuco, and Ojochal, from April 2013 to September 2014. We used DNA barcoding techniques, utilizing a 1044 base pair region of the NADH dehydrogenase subunit 2 gene, to identify to species 275 of the 416 samples collected. Within these fisheries, seven species of shark and one ray were identified, with the scalloped hammerhead shark (Sphyrna lewini) accounting for ~750-80% of all sharks landed. Observed total lengths (TL) for the scalloped hammerhead shark (10.9–99 cm) in these fisheries suggests the sharks sampled were all either juveniles or neonates. Based on these data it is likely that the areas from which these samples were collected represent nursery grounds for the scalloped hammerhead shark. The quantity of young scalloped hammerhead sharks removed from these areas, and ones similar to them, by these artisanal fisheries could be of great importance when determining future conservation measures for this species. We conclude our findings also indicate that sharks caught in these artisanal fisheries do not appear to represent those sold in markets around San Jose.

59 BASIC BIOLOGICAL SCIENCES↗

CFD modeling of non-catalytic, partial-oxidation engine reformer for flare mitigation

Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.

Computational Fluid Dynamics↗

Time-resolved spray characterization via unified optical flow and binarization technique

This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.

42 ENGINEERING↗

Dynamically robust coordinated set point tracking of distributed DERs at point of common coupling

Low-inertia operation of small-scale power systems, such as a microgrid or a portion of a long feeder, requires careful coordination of the controller performance of the constituting devices. This challenge is exacerbated in microgrids serving the functionalities of a conventional synchronous-based generation unit while comprised of smaller DERs operating mainly interfaced through power electronics converters. This paper builds on the idea of set point modulation and proposes a two-level control strategy that aims to achieve superior performance at the point of common coupling (PCC) of microgrids by combining a local control level with a distributed and coordinated level. Several case studies on both AC and DC systems, the CIGRE low-voltage benchmark system as the AC system and a test DC microgrid, validate the performance of the proposed approach. The real-world applicability of the approach is established via a high-fidelity power hardware-in-the-loop (PHIL) experimental setup and an application case study on grid frequency regulation. The proposed approach enables a microgrid to participate in ancillary service provisions where speed and quality of regulation are critical.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Study of the film boiling heat transfer and two-phase flow interface behavior using image processing

Here, in this study, based on a small-scale quench test facility, the two-phase flow interface behavior during quench transients is visualized and analyzed utilizing an image processing framework. The high-fidelity experimental results obtained for two-phase flow in the current framework can support various studies both in the time domain and in the frequency domain. In particular, visualization of the data obtained from different heating surfaces under different test conditions are used to perform a full-scale transient 2-D vapor film reconstruction. The liquid-vapor interface variations in various heat transfer regimes as well as at the initial film breakup point can be directly obtained through the processed data. Moreover, the temporal variation of the interfacial wave frequency approaching quench is investigated in detail. Based on the high-resolution data obtained for the liquid-vapor interface, the detailed phase velocity and temperature profiles are obtained through theoretic analysis, based on which the film boiling heat transfer coefficient (HTC) can be determined. In addition, an improved film boiling HTC model is developed considering the effects of wall superheat, liquid subcooling temperature, vapor film thickness as well as fluid properties. The model is found to predict film boiling HTC well within 15% error.

42 ENGINEERING↗

Design, optimization, and validation of a triply periodic minimal surface based heat exchanger for extreme temperature applications

Heat exchanger (HX) innovation offers potential for significant improvements in energy efficiency for a host of applications including but not limited to aviation and power generation cycles. Triply Periodic Minimal Surfaces (TPMS) have received significant attention in recent years due to their incredibly high surface area density, which makes them very attractive from a heat transfer point of view. Recent efforts have largely focused on thermal-hydraulic characterization of the many available TPMS and the testing of small-scale HX prototypes. However, practical implementation remains largely unexplored, partially due to the extreme computational cost associated with accurately simulating these complex structures. In this work, we present the design, simulation, and optimization of a TPMS-HX for high temperature (900 °C) and pressure (25 MPa) applications. Detailed analysis of HX sub-sections is conducted to define the smallest repeatable section which may be used to characterize the thermal-hydraulic performance of the entire HX, enabling rapid design and iteration with significantly reduced computational cost. Compared to preliminary results for a water-to-water experiment, calibrated heat transfer and pressure drop predictions were within ±5 % and ±10 %, respectively. Optimization results show a 10x increase in volumetric power density over the initial design, which is verified against a parametric exhaustive search of the HX design space. Furthermore, it was found that reducing the unit cell hydraulic diameter cell plays the largest role in increasing heat transfer, increasing the surface area density and enabling a more compact and efficient HX.

42 ENGINEERING↗

The cold high-pressure approach to hydrogen delivery

In view of the very expensive and wasteful nature of today's approaches to H 2 delivery, in this work we explore the possibility of transporting cold (200 K) high pressure (875 bar) H 2 in thermally insulated trailers and dispensing H 2 directly from the trailer, with the potential to eliminate station compressor, cascade, and refrigerator, leading to major reductions in station complexity, maintenance, electricity consumption, and cost, while improving functionality by enabling essentially unlimited back to back refuels, and improving safety due to reduced H 2 expansion energy at low temperature. Detailed techno-economic analysis shows promise for substantial delivery cost reductions through cold high pressure H 2 dispensed directly from the trailer. Results indicate that: (1) Terminal operations for cold high pressure H 2 delivery are $\$$0.32/kg H 2 more expensive than for 350 bar compressed gas delivery (today's lowest cost H 2 delivery technology) due to higher level of pressurization (to 1000 bar) and chilling needs (to 165 K). (2) Trailer cost drops slightly ($\$$0.73 vs. $\$$0.81/kg H 2 for a 350 bar trailer) due to increased capacity (1035 kg H 2 delivered vs. 700 kg) compensating for increased capital cost ($\$$906,900 for cold high pressure H 2 vs. $\$$634,000 for 350 bar trailer). (3) Cold hydrogen delivery presents major advantages in fueling station cost, reduced from $\$$1.27 to $\$$0.46/kg H 2 due to elimination of major system components: compressor, cascade, and chiller. (4) Total compression cost (terminal + station) drops from $\$$0.92/kg H 2 ($\$$0.32 terminal and $\$$0.60 station) for 350 bar trailers to $\$$0.55/kg H 2 (all at the terminal) for cold high pressure H 2 . (5) Elimination of small-scale station compressors is the main contributor to reduced delivery cost due to their inefficiency, capital expense, and maintenance needs. In summary, total delivery cost reduction vs. 350 bar trailer equals $\$$0.58/kg H 2 (from $\$$2.96 to 2.38/kg H 2 ), equivalent to 24% of the total delivery cost. This large cost advantage will improve the economics of H 2 vehicles facilitating the transition to a future of zero emission transportation.

08 HYDROGEN↗